Essbase Analytic Services

Essbase Analytic ServicesRelease 7.1

Database Administrators Guides:Volume I: Designing and Creating Analytic Services Databases Volume II: Loading, Calculating, and Retrieving Data Volume III: Optimization and System Administration Volume IV: Creating, Calculating, and Managing Aggregate Storage Databases

Hyperion Solutions CorporationP/N: D116565000

Copyright 19962004 Hyperion Solutions Corporation. All rights reserved. May be protected by Hyperion Patents, including U.S. 5,359,724 and U.S. 6,317,750 Hyperion, the Hyperion H logo and Hyperions product names are trademarks of Hyperion. References to other companies and their products use trademarks owned by the respective companies and are for reference purpose only. No portion of this manual may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or information storage and retrieval systems, for any purpose other than the purchasers personal use, without the express written permission of Hyperion. The information contained in this manual is subject to change without notice. Hyperion shall not be liable for errors contained herein or consequential damages in connection with the furnishing, performance, or use of this material. This software described in this manual is licensed exclusively subject to the conditions set forth in the Hyperion license agreement. Please read and agree to all terms before using this software. GOVERNMENT RIGHTS LEGEND: Use, duplication or disclosure by the U.S. Government is subject to restrictions set forth in the applicable Hyperion license agreement and as provided in DFARS 227.7202-1(a) and 227.7202-3(a) (1995), DFARS 252.227-7013(c)(1)(ii) (Oct 1988), FAR 12.212(a) (1995), FAR 52.227-19, or FAR 52.227-14, as applicable. Hyperion Solutions Corporation 1344 Crossman Avenue Sunnyvale, California 94089 Printed in the U.S.A..

Essbase Analytic ServicesRelease 7.1

Database Administrators GuideVolume I: Designing and Creating Analytic Services Databases

Hyperion Solutions Corporation

Copyright 19962004 Hyperion Solutions Corporation. All rights reserved. May be protected by Hyperion Patents, including U.S. 5,359,724 and U.S. 6,317,750 Hyperion, the Hyperion H logo and Hyperions product names are trademarks of Hyperion. References to other companies and their products use trademarks owned by the respective companies and are for reference purpose only. No portion of this manual may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or information storage and retrieval systems, for any purpose other than the purchasers personal use, without the express written permission of Hyperion. The information contained in this manual is subject to change without notice. Hyperion shall not be liable for errors contained herein or consequential damages in connection with the furnishing, performance, or use of this material. This software described in this manual is licensed exclusively subject to the conditions set forth in the Hyperion license agreement. Please read and agree to all terms before using this software. GOVERNMENT RIGHTS LEGEND: Use, duplication or disclosure by the U.S. Government is subject to restrictions set forth in the applicable Hyperion license agreement and as provided in DFARS 227.7202-1(a) and 227.7202-3(a) (1995), DFARS 252.227-7013(c)(1)(ii) (Oct 1988), FAR 12.212(a) (1995), FAR 52.227-19, or FAR 52.227-14, as applicable. Hyperion Solutions Corporation 1344 Crossman Avenue Sunnyvale, California 94089 Printed in the U.S.A..

Contents

Preface ......................................................................................................................... xvPurpose ............................................................................................................................. xv Audience .......................................................................................................................... xv Document Structure ........................................................................................................ xvi Where to Find Documentation ........................................................................................ xvi Conventions.................................................................................................................... xvii Additional Support .......................................................................................................... xix Documentation Feedback................................................................................................ xix

Part I: Understanding Essbase Analytic Services................................. 21 Chapter 1: Introducing Hyperion Essbase ............................................... 23Key Features..................................................................................................................... Integration with Existing Infrastructure ................................................................... Data Integration ........................................................................................................ Ease of Server and Database Administration ........................................................... Mission Critical Applications in Web-based Environments..................................... Powerful Querying ................................................................................................... Calculations .............................................................................................................. Write-Back and Security .......................................................................................... Ease of Development................................................................................................ Essbase Product Components .......................................................................................... Analytic Services...................................................................................................... Administration Services ........................................................................................... Deployment Services................................................................................................ Spreadsheet Products and Hyperion Analyzer ......................................................... 24 24 24 24 25 25 25 25 26 27 27 28 28 29

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Contents

Integration Services................................................................................................... 29 Application Programming Interface (API)................................................................ 29 Developer Products ................................................................................................... 29 Data Mining .............................................................................................................. 30

Chapter 2: Understanding Multidimensional Databases.................... 31OLAP and Multidimensional Databases .......................................................................... 31 Dimensions and Members ................................................................................................ 33 Outline Hierarchies ................................................................................................... 34 Dimension and Member Relationships ..................................................................... 35 Parents, Children, and Siblings......................................................................... 35 Descendants and Ancestors .............................................................................. 36 Roots and Leaves .............................................................................................. 36 Generations and Levels..................................................................................... 36 Standard Dimensions and Attribute Dimensions ...................................................... 37 Sparse and Dense Dimensions .................................................................................. 38 Selection of Dense and Sparse Dimensions .............................................................. 39 Dense-Sparse Configuration for Sample Basic................................................. 40 Dense and Sparse Selection Scenario ............................................................... 41 Data Storage...................................................................................................................... 44 Data Values ............................................................................................................... 45 Data Blocks and the Index System............................................................................ 46 Multiple Data Views ................................................................................................. 50

Chapter 3: Quick Start for Implementing Analytic Services ............. 53 Chapter 4: Basic Architectural Elements ................................................... 61Attribute Dimensions and Standard Dimensions.............................................................. 61 Sparse and Dense Dimensions.......................................................................................... 62 Data Blocks and the Index System ................................................................................... 64 Selection of Sparse and Dense Dimensions...................................................................... 68 Determining the Sparse-Dense Configuration for Sample Basic.............................. 68 Dense and Sparse Selection Scenarios ............................................................................. 70 Scenario 1: All Sparse Standard Dimensions ........................................................... 70 Scenario 2: All Dense Standard Dimensions ............................................................ 71

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Scenario 3: Dense and Sparse Standard Dimensions................................................ 72 Scenario 4: A Typical Multidimensional Problem ................................................... 72 The Analytic Services Solution ........................................................................................ 75

Chapter 5: Case Study: Designing a Single-Server, Multidimensional Database ............................................................................... 77Process for Designing a Database .................................................................................... 78 Case Study: The Beverage Company ............................................................................... 79 Analyzing and Planning ................................................................................................... 80 Analyzing Source Data ............................................................................................. 81 Identifying User Requirements................................................................................. 82 Planning for Security in a Multiple User Environment ............................................ 82 Creating Database Models ........................................................................................ 82 Identifying Analysis Objectives ....................................................................... 83 Determining Dimensions and Members ........................................................... 83 Analyzing Database Design ............................................................................. 88 Drafting Outlines .............................................................................................................. 95 Dimension and Member Properties .......................................................................... 97 Dimension Types ...................................................................................................... 97 Member Storage Properties ...................................................................................... 99 Checklist for Dimension and Member Properties................................................... 100 Designing an Outline to Optimize Performance..................................................... 100 Optimizing Query Performance ..................................................................... 100 Optimizing Calculation Performance ............................................................. 101 Meeting the Needs of Both Calculation and Retrieval ................................... 102 Checking System Requirements..................................................................................... 102 Loading Test Data........................................................................................................... 103 Defining Calculations ..................................................................................................... 103 Consolidation of Dimensions and Members........................................................... 104 Effect of Position and Operator on Consolidation.......................................... 105 Consolidation of Shared Members ................................................................. 106 Checklist for Consolidation ............................................................................ 107 Tags and Operators on Example Measures Dimension .......................................... 107


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Contents

Accounts Dimension Calculations .......................................................................... 108 Time Balance Properties ................................................................................. 108 Variance Reporting ......................................................................................... 110 Formulas and Functions .......................................................................................... 110 Dynamic Calculations ............................................................................................. 112 Two-Pass Calculations ............................................................................................ 113 Checklist for Calculations ....................................................................................... 114 Defining Reports............................................................................................................. 115 Verifying the Design ....................................................................................................... 116

Chapter 6: About Essbase Administration Services .......................... 117Administration Services Architecture............................................................................. 117 Deploying Administration Services................................................................................ 118 Starting Administration Services .................................................................................... 119 About Administration Services Users ............................................................................ 119 Connecting to Administration Services .......................................................................... 119 Adding Administration Servers to Enterprise View ....................................................... 120 Adding Analytic Servers to Enterprise View.................................................................. 120 About Analytic Server Connections and Ports ............................................................... 121 About Administration Server.......................................................................................... 121

Part II: Designing and Creating Applications and Databases ....... 123 Chapter 7: Creating Applications and Databases ................................ 125Process for Creating Applications and Databases .......................................................... 126 Understanding Applications and Databases ................................................................... 126 Understanding Database Objects .................................................................................... 127 Understanding Database Outlines ........................................................................... 128 Understanding Data Sources ................................................................................... 128 Understanding Rules Files for Data Load and Dimension Build............................ 128 Understanding Calculation Scripts.......................................................................... 129 Understanding Report Scripts ................................................................................. 129 Understanding Security Definitions........................................................................ 129 Understanding Linked Reporting Objects............................................................... 130 Understanding Spreadsheet Queries ....................................................................... 130

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Contents

Understanding Member Select Definitions............................................................. Understanding Triggers Definitions........................................................................ Creating Applications and Databases............................................................................. Creating a New Application ................................................................................... Creating a New Database........................................................................................ Annotating a Database ............................................................................................ Rules for Naming Applications and Databases ...................................................... Using Substitution Variables .......................................................................................... Rules for Setting Substitution Variable Names and Values .................................... Setting Substitution Variables................................................................................. Deleting Substitution Variables .............................................................................. Updating Substitution Variables ............................................................................. Copying Substitution Variables .............................................................................. Using Location Aliases................................................................................................... Creating Location Aliases....................................................................................... Editing or Deleting Location Aliases......................................................................

130 130 131 131 132 132 133 133 134 135 135 135 136 136 137 137

Chapter 8: Creating and Changing Database Outlines ..................... 139Process for Creating Outlines......................................................................................... Creating and Editing Outlines ........................................................................................ Locking and Unlocking Outlines.................................................................................... Adding Dimensions and Members to an Outline ........................................................... Understanding the Rules for Naming Dimensions and Members .................................. Setting Data Storage Properties...................................................................................... Positioning Dimensions and Members........................................................................... Moving Dimensions and Members......................................................................... Sorting Dimensions and Members.......................................................................... Verifying Outlines .......................................................................................................... Saving Outlines .............................................................................................................. Saving an Outline with Added Standard Dimensions ............................................ Saving an Outline with One or More Deleted Standard Dimensions ..................... Creating Sub-Databases Using Deleted Members.................................................. 140 140 142 143 143 146 147 147 148 148 150 151 151 151


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Contents

Chapter 9: Setting Dimension and Member Properties .................... 153Setting Dimension Types ................................................................................................ 154 Creating a Time Dimension .................................................................................... 154 Creating an Accounts Dimension ........................................................................... 155 Setting Time Balance Properties..................................................................... 155 Setting Skip Properties.................................................................................... 157 Setting Variance Reporting Properties ............................................................ 158 Setting Analytic Services Currency Conversion Properties............................ 159 Creating a Country Dimension ............................................................................... 159 Creating Currency Partitions................................................................................... 159 Creating Attribute Dimensions ............................................................................... 160 Setting Member Consolidation ....................................................................................... 160 Calculating Members with Different Operators ............................................................. 161 Determining How Members Store Data Values.............................................................. 162 Understanding Stored Members.............................................................................. 163 Understanding Dynamic Calculation Members ...................................................... 163 Understanding Label Only Members ...................................................................... 164 Understanding Shared Members............................................................................. 164 Understanding the Rules for Shared Members ............................................... 165 Understanding Shared Member Retrieval During Drill-Down....................... 166 Understanding Implied Sharing ...................................................................... 168 Setting Aliases ................................................................................................................ 169 Alias Tables............................................................................................................. 170 Creating Aliases ...................................................................................................... 170 Creating and Managing Alias Tables ...................................................................... 171 Creating a New Alias Table ............................................................................ 171 Setting an Alias Table as Active ..................................................................... 171 Copying an Alias Table................................................................................... 172 Renaming an Alias Table ................................................................................ 172 Clearing and Deleting Alias Tables ................................................................ 173 Importing and Exporting Alias Tables ............................................................ 173 Setting Two-Pass Calculations........................................................................................ 174 Creating Formulas........................................................................................................... 175 Naming Generations and Levels..................................................................................... 175

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Creating UDAs ............................................................................................................... 176 Adding Comments.......................................................................................................... 177

Chapter 10: Working with Attributes .......................................................... 179Process for Creating Attributes ...................................................................................... Understanding Attributes................................................................................................ Understanding Attribute Dimensions ............................................................................. Understanding Members of Attribute Dimensions ................................................. Understanding the Rules for Base and Attribute Dimensions and Members ......... Understanding the Rules for Attribute Dimension Association ............................. Understanding the Rules for Attribute Member Association ................................. Understanding Attribute Types ............................................................................... Comparing Attribute and Standard Dimensions ..................................................... Comparing Attributes and UDAs............................................................................ Designing Attribute Dimensions .................................................................................... Using Attribute Dimensions ................................................................................... Using Alternative Design Approaches.................................................................... Optimizing Outline Performance............................................................................ Building Attribute Dimensions....................................................................................... Setting Member Names in Attribute Dimensions .......................................................... Setting Prefix and Suffix Formats for Member Names of Attribute Dimensions ........................................................................................... Setting Boolean Attribute Member Names............................................................. Changing the Member Names in Date Attribute Dimensions ................................ Setting Up Member Names Representing Ranges of Values.................................. Changing the Member Names of the Attribute Calculations Dimension ............... Calculating Attribute Data.............................................................................................. Understanding the Attribute Calculations Dimension ............................................ Understanding the Default Attribute Calculations Members.................................. Viewing an Attribute Calculation Example ............................................................ Accessing Attribute Calculations Members Using the Spreadsheet....................... Optimizing Calculation and Retrieval Performance ............................................... Using Attributes in Calculation Formulas .............................................................. Understanding Attribute Calculation and Shared Members ................................... 180 180 182 183 183 184 185 187 188 190 192 193 193 195 195 196 196 197 198 198 200 200 201 203 204 205 205 206 208


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Contents

Chapter 11: Linking Objects to Analytic Services Data .................... 209Understanding LROs ...................................................................................................... 209 Understanding LRO Types and Data Cells ..................................................................... 210 Setting Up Permissions for LROs................................................................................... 211 Viewing and Deleting LROs ........................................................................................... 212 Exporting and Importing LROs ...................................................................................... 213 Limiting LRO File Sizes for Storage Conservation........................................................ 214

Chapter 12: Designing and Building Currency Conversion Applications ............................................................................................................. 215About the Sample Currency Application........................................................................ 216 Structure of Currency Applications ................................................................................ 217 Main Database......................................................................................................... 217 Currency Database .................................................................................................. 220 Conversion Methods ....................................................................................................... 222 Building Currency Conversion Applications and Performing Conversions ................... 222 Creating Main Database Outlines ........................................................................... 223 Preparing Main Database Outlines ......................................................................... 223 Generating Currency Database Outlines................................................................. 224 Linking Main and Currency Databases................................................................... 224 Converting Currency Values ................................................................................... 224 Overwriting Local Values with Converted Values .......................................... 225 Keeping Local and Converted Values ............................................................. 225 Calculating Databases..................................................................................... 227 Converting Currencies in Report Scripts ........................................................ 228 Tracking Currency Conversions.............................................................................. 229 Reasons to Turn Off CCTRACK .................................................................... 230 Methods for Turning Off CCTRACK ............................................................. 230 Troubleshooting Currency Conversion ................................................................... 231

Chapter 13: Designing Partitioned Applications .................................. 233Process for Designing a Partitioned Database ................................................................ 234 Understanding Analytic Services Partitioning................................................................ 234 What Is a Partition?................................................................................................. 235 Data Sources and Data Targets................................................................................ 236

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Contents

Overlapping Partitions ............................................................................................ Attributes in Partitions ............................................................................................ Deciding Whether to Partition a Database ..................................................................... When to Partition a Database.................................................................................. When Not to Partition a Database........................................................................... Determining Which Data to Partition............................................................................. Deciding Which Type of Partition to Use ...................................................................... Replicated Partitions ............................................................................................... Rules for Replicated Partitions ....................................................................... Advantages and Disadvantages of Replicated Partitions................................ Performance Considerations for Replicated Partitions................................... Replicated Partitions and Port Usage ............................................................. Transparent Partitions ............................................................................................. Rules for Transparent Partitions ..................................................................... Advantages and Disadvantages of Transparent Partitions.............................. Performance Considerations for Transparent Partitions................................. Calculating Transparent Partitions ................................................................. Performance Considerations for Transparent Partition Calculations ............. Transparent Partitions and Member Formulas................................................ Transparent Partitions and Port Usage ........................................................... Linked Partitions..................................................................................................... Advantages and Disadvantages of Linked Partitions ..................................... Drill Across and Linked Partitions ................................................................. Linked Partitions and Port Usage ................................................................... Choosing a Partition Type....................................................................................... Planning for Security for Partitioned Databases ............................................................ Process for Setting up End User Security............................................................... Process for Setting up Administrator Security ....................................................... Case Studies for Designing Partitioned Databases......................................................... Case Study 1: Partitioning an Existing Database.................................................... Case Study 2: Connecting Existing Related Databases .......................................... Case Study 3: Linking Two Databases ...................................................................

238 238 239 240 240 241 242 242 243 245 246 247 248 249 251 253 253 254 255 255 256 258 258 259 260 261 261 261 262 262 265 266


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Contents

Chapter 14: Creating and Maintaining Partitions ................................. 269Process for Creating Partitions ....................................................................................... 270 Choosing a Partition Type ....................................................................................... 271 Setting up the Data Source and the Data Target...................................................... 271 Setting the User Name and Password ..................................................................... 272 Defining a Partition Area ........................................................................................ 273 Mapping Members .................................................................................................. 273 Mapping Members with Different Names ...................................................... 274 Mapping Data Cubes with Extra Dimensions................................................. 275 Mapping Shared Members.............................................................................. 276 Importing Member Mappings ......................................................................... 277 Mapping Attributes Associated with Members .............................................. 277 Creating Advanced Area-Specific Mappings ................................................. 279 Validating Partitions ................................................................................................ 281 Saving Partitions ..................................................................................................... 283 Process for Maintaining Partitions.................................................................................. 283 Testing Partitions..................................................................................................... 283 Synchronizing Outlines........................................................................................... 284 Setting the Source Outline and the Target Outline ......................................... 284 Performing Outline Synchronization .............................................................. 286 Tracking Changes ........................................................................................... 286 Updating Shared Members During Outline Synchronization......................... 287 Populating or Updating Replicated Partitions......................................................... 289 Editing and Deleting Partitions ............................................................................... 290 Viewing Partition Information ................................................................................ 291 Troubleshooting Partitions ...................................................................................... 291

Chapter 15: Accessing Relational Data with Hybrid Analysis....... 293Understanding Hybrid Analysis ..................................................................................... 294 Hybrid Analysis Relational Source......................................................................... 294 Data Retrieval.......................................................................................................... 295 Hybrid Analysis Guidelines .................................................................................... 296 Defining Hybrid Analysis Relational Sources................................................................ 297

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Contents

Retrieving Hybrid Analysis Data ................................................................................... Retrieving Hybrid Analysis Data with Spreadsheet Add-in ................................... Supported Drill-Down Options in Hybrid Analysis ....................................... Supported Drill-Up Option in Hybrid Analysis ............................................. Retrieving Hybrid Analysis Data with Report Writer ............................................ Retrieving Hybrid Analysis Data with Hyperion Analyzer.................................... Using Outline Editor with Hybrid Analysis ................................................................... Managing Data Consistency........................................................................................... Managing Security in Hybrid Analysis .......................................................................... Using Formulas with Hybrid Analysis ........................................................................... Unsupported Functions in Hybrid Analysis ................................................................... Relationship Functions ........................................................................................... Member Conditions Functions ............................................................................... Range Functions ..................................................................................................... Attribute Functions ................................................................................................. Current Member and XREF Functions...................................................................

298 299 299 299 300 300 301 302 303 304 305 305 305 306 306 306

Index ............................................................................................................................ 307


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Preface

Welcome to the Essbase Analytic Services Database Administrators Guide. This preface discusses the following topics:

Purpose on page xv Audience on page xv Document Structure on page xvi Where to Find Documentation on page xvi Conventions on page xvii Additional Support on page xix

PurposeThis guide provides you with all the information that you need to implement, design, and maintain an optimized Essbase Analytic Services multidimensional database. It explains the Analytic Services features and options, and contains the concepts, processes, and examples that you need to use the software.

AudienceThis guide is for database administrators or system administrators who are responsible for designing, creating, and maintaining applications, databases, and database objects (for example, data load rules, and calculation scripts).


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Preface

Document StructureThis document contains the following information:

Chapters 1 through 14 (Volume I) contain information on designing and creating Analytic Services databases, including information on converting currencies, partitioning applications, and accessing relational data using the hybrid analysis feature. Chapters 15 through 34 (Volume II) contain information on building dimensions and loading data, calculating data, and retrieving data. Chapters 35 through 56 (Volume III) contain information on designing and managing a security system, maintaining, backing up, and optimizing Analytic Services databases, and includes a glossary of key terms and their definitions. Chapters 57 through 60 (Volume IV) contain information on aggregate storage databases.

Where to Find DocumentationAll Analytic Services documentation is accessible from the following locations:

The HTML Information Map is located atinstallation_directory\docs\esb_infomap.htm, where installation_directory is the directory in which you have installed the Analytic Services documentation.

The Hyperion Solutions Web site is located at http://www.hyperion.com. The Hyperion Download Center can be accessed from http://hyperion.subscribenet.com or from http://www.hyperion.com.

To access documentation from the Hyperion Solutions Web site:1. Log on to http://www.hyperion.com. 2. Select the Support link and type your username and password to log on.Note: New users must register to receive a username and password.

3. Click the Hyperion Download Center link and follow the on-screen instructions.

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Conventions

To access documentation from the Hyperion Download Center:1. Log on to http://hyperion.subscribenet.com. 2. In the Login ID and Password text boxes, enter your assigned login ID name and password. Then click Login. 3. If you are a member on multiple Hyperion Download Center accounts, select the account that you want to use for the current session. 4. Follow the on-screen instructions. 5. Perform one of the following actions:

To access documentation online, from the Product List, select the appropriate product and follow the on-screen instructions. To order printed documentation, from the Information section in the left frame, select Order Printed Documentation, then follow the on-screen instructions

To order printed documentation if you do not have access to the HyperionDownload Center:

In the United States, call Hyperion Solutions Customer Support at 877-901-4975. From outside the United States, including Canada, call Hyperion Solutions Customer Support at 203-703-3600. Clients who are not serviced by support from North America should call their local support centers.

ConventionsThe following table shows the conventions that are used in this document:Table i: Conventions Used in This DocumentItem Meaning

Brackets []

Arrows indicate the beginning of procedures consisting of sequential steps or one-step procedures. In examples, brackets indicate that the enclosed elements are optional.


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Preface

Table i: Conventions Used in This Document (Continued)Item Meaning

Bold CAPITAL LETTERS Ctrl + 0

Bold in procedural steps highlights major interface elements. Capital letters denote commands and various IDs. (Example: CLEARBLOCK command) Keystroke combinations shown with the plus sign (+) indicate that you should press the first key and hold it while you press the next key. Do not type the plus sign. Courier font indicates that the example text is code or syntax. Courier italic text indicates a variable field in command syntax. Substitute a value in place of the variable shown in Courier italics. When you see the environment variable ARBORPATH in italics, substitute the value of ARBORPATH from your site. Italic n stands for a variable number; italic x can stand for a variable number or an alphabet. These variables are sometimes found in formulas. Ellipsis points indicate that text has been omitted from an example. This document provides examples and procedures using a right-handed mouse. If you use a left-handed mouse, adjust the procedures accordingly. Options in menus are shown in the following format. Substitute the appropriate option names in the placeholders, as indicated. Menu name > Menu command > Extended menu command For example: 1. Select File > Desktop > Accounts.

Example text Courier italics

ARBORPATH

n, x

Ellipses (...) Mouse orientation

Menu options

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Additional Support

Additional SupportIn addition to providing documentation and online help, Hyperion offers the following product information and support. For details on education, consulting, or support options, click the Services link on the Hyperion Web site at http://www.hyperion.com.

Education ServicesHyperion offers instructor-led training, custom training, and eTraining covering all Hyperion applications and technologies. Training is geared to administrators, end users, and information systems (IS) professionals.

Consulting ServicesExperienced Hyperion consultants and partners implement software solutions tailored to clients particular reporting, analysis, modeling, and planning requirements. Hyperion also offers specialized consulting packages, technical assessments, and integration solutions.

Technical SupportHyperion provides enhanced electronic-based and telephone support to clients to resolve product issues quickly and accurately. This support is available for all Hyperion products at no additional cost to clients with current maintenance agreements.

Documentation FeedbackHyperion strives to provide complete and accurate documentation. We value your opinions on this documentation and want to hear from you. Send us your comments by clicking the link for the Documentation Survey, which is located on the Information Map for your product.


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Preface

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Part

I

Understanding Essbase Analytic Services

Part I: Understanding Essbase Analytic Services

Part I introduces you to Essbase Analytic Services by describing general online analytical processing (OLAP) concepts, basic multidimensional concepts, the Analytic Services architecture, and how to design both single server and partitioned applications. Part I contains the following chapters: Chapter 1, Introducing Hyperion Essbase, describes the parts of Analytic Services, high-level Analytic Services functionality, key architectural features, and how Analytic Services works in a client-server environment. Chapter 2, Understanding Multidimensional Databases, introduces you to basic multidimensional concepts and terminology, including dimensions and members, data values, and hierarchies. Chapter 4, Basic Architectural Elements, describes how the Analytic Services architecture stores and retrieves information. Chapter 3, Quick Start for Implementing Analytic Services, provides a high-level process map for implementing Analytic Services in your organization with cross references to further information. Chapter 5, Case Study: Designing a Single-Server, Multidimensional Database, uses the Sample Basic database to present rules you should use to design a single-server, multidimensional database solution. Chapter 6, About Essbase Administration Services, describes the client interfaces to Analytic Services, focussing on Administration Services, the new cross-platform administration tool for Analytic Services.


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Understanding Essbase Analytic Services

22


1Chapter

1

Introducing Hyperion Essbase

This chapter provides an architectural overview of the product components and introduces the key features of Essbase products, including: Essbase Analytic Services Essbase Deployment Services Essbase Administration Services Essbase Spreadsheet Services Essbase Integration Services

Essbase products provide companies with the ability to deliver critical business information to the right people when they need it. With Essbase, companies quickly leverage and integrate data from multiple existing data sources and distribute filtered information to end-user communities in the format that best meets the users needs. Users interact and intuitively explore data in real-time and along familiar business dimensions, enabling them to perform speed-of-thought analytics. This chapter contains the following sections:

Key Features on page 24 Essbase Product Components on page 27


23


Key FeaturesEssbase products provide the analytic solution that integrates data from multiple sources and meets the needs of users across an enterprise. Essbase products enable the quick and easy implementation of solutions, add value to previously inaccessible data, and transform data into actionable information.

Integration with Existing InfrastructureEssbase products integrate with your existing business intelligence infrastructure. Essbase products meet the enterprise analytic demands of users for critical business information with a minimum of information technology (IT) overhead and thus enable organizations to realize maximum return on their existing IT investments:

Provides an extensible architecture Supports a comprehensive range of data sources, hardware and operating system platforms, access interfaces, and development languages Enables analytic applications to be deployed across a local or wide area network and across an intranet or Internet

Data IntegrationEssbase products enable organizations to leverage data in their data warehouses, legacy systems, online transaction processing (OLTP) systems, enterprise resource planning (ERP) systems, e-business systems, customer relationship management (CRM) applications, Web log files and other external data sources. For database integration, Essbase Integration Services provides a suite of graphical tools, data integration services, and a metadata catalog that tie into relational databases or data warehouse environments (including SAP BW).

Ease of Server and Database AdministrationEssbase products provide a cross-platform administration console. The console gives you detailed control over the Essbase environment:

You can manage multiple servers and databases. You can use MaxL, a syntactical language command shell with a PERL extension module, to automate batch maintenance.

24


Key Features

1Mission Critical Applications in Web-based EnvironmentsA middle-tier framework extends the power of Essbase products by creating a Web-enabled, distributed platform for Essbase applications hence serving the analysis needs of large numbers of users in Web-based environments. Essbase Deployment Services provide connection pooling, clustering, and failover support, which extend the scalability and reliability of the platform and support mission-critical applications in a 24 x 7 environment.

Powerful QueryingLarge communities of business users can interact with data in real time, analyzing business performance at the speed of thought. Using Essbase products you can organize and present data along familiar business dimensions, thus enabling users to view and explore the data intuitively and to turn the data into actionable information.

CalculationsEssbase Analytic Services includes powerful calculation features for demanding analytic requirements. A rich library of functions makes it easy to define advanced and sophisticated business logic and relationships. Analytic Services gives users the flexibility to build, customize and extend the calculator through custom-defined macros and functions, as well as the ability to span calculations across databases. On multiprocessor systems, a database administrator can configure a single calculation request to use multiple threads to accomplish the calculation, providing enhanced calculation speed. Aggregate storage databases provide an alternative to block storage databases, and enable dramatic improvements in database aggregation time for certain types of applications.

Write-Back and SecurityAnalytic Services provides unique multi-user read and write capabilities, including data update and multi-user recalculation. Business users with front-end tools can write data back to a server and recalculate the data on a server using calculation scripts key functionality to support sophisticated modeling and planning applications.


25


The robust, multi-level security model provides server-, database-, and cell-level security. Full control of data access, views, and write capabilities are managed through administration. Integration with external authentication systems, such as Lightweight Directory Access Protocol (LDAP), allows the quick creation of security models and reduces the time and the cost of application development and maintenance.

Ease of DevelopmentAnalytic Services offers many key advantages to help users develop effective multi-dimensional applications. Users can:

Design and manage applications using a graphical interface to control most server functions. Quickly add dimensions, change calculations, and modify hierarchies to reflect new business developments. In addition, the dynamic dimension builder automatically defines and dynamically loads large amounts of data, including data from spreadsheets, flat files, and supported relational database tables directly into a database. Define key calculations without having to write a program. Define security for individuals and groups and customize views and retrieval procedures for each user without writing a program.

For information about supported applications, operating systems, and networking protocols, see the Essbase Analytic Services Installation Guide.

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Essbase Product Components

1

Essbase Product ComponentsEssbase products incorporate powerful architectural features to handle a wide range of analytic applications across large multi-user environments. Figure 1 provides a high-level view of the information flow between the source data and the product components.Figure 1: High-level Information Flow Between Product Components

Note: For information on Hyperion Objects, Hyperion Analyzer, and Hyperion Application Link (HAL) visit our website at www.hyperion.com.

Analytic ServicesAnalytic Servicesa multi-threaded OLAP database software that takes advantage of symmetric multi processing hardware platformsis based upon Web-deployable, thin-client architecture. The server acts as a shared resource, handling all data storage, caching, calculations, and data security. The Analytic Server client needs only to retrieve and view data that resides on a server.


27


All Analytic Services application components, including database outlines and calculation scripts, application control, and multi-dimensional database information, reside on a server. With Analytic Services you can configure server disk storage to span multiple disk drives, enabling you to store large databases. Analytic Services requires a server to run a multi-threaded operating system so a server can efficiently manage multiple, simultaneous requests. A server also runs a server agent process that acts as a traffic coordinator for all user requests to applications.Aggregate storage databasesusing a new storage kernel for multidimensional databasesprovide an alternative to block storage databases, and enable dramatic increases in database dimensionality. Using aggregate storage, Analytic Services serves a wide range of analytic needsfinancial analysis, planning, budgeting, sales analysis, marketing analysis, supply chain analysis, profitability analyticsall from a single analytic infrastructure. MaxLa multidimensional database access language that is part of Analytic Serverprovides a flexible way to automate Analytic Services administration and maintenance tasks. See dev.hyperion.com or the Essbase Analytic Services Installation Guide for information on the supported operating systems, and for specific information about server configuration requirements.

Administration ServicesAdministration Servicesthe database and system administrators interface to Analytic Servicesprovides a single-point-of-access console to multiple Analytic Servers. Using Administration Services you can design, develop, maintain, and manage multiple Analytic Servers, applications, and databases. You can preview data from within the console, without having to open a client application such as Spreadsheet Add-in. You can also use custom Java plug-ins to leverage and extend key functionality.

Deployment ServicesDeployment Services allows multiple instances of Analytic Server to run on multiple machines, while serving the user as one logical unit and removing and single point of failure. Deployment Services enables database clustering with load balancing and fail-over capabilities.

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Essbase Product Components

1Spreadsheet Products and Hyperion AnalyzerHyperion Analyzer, Spreadsheet Services, and Spreadsheet Add-inthe business users interface to Analytic Servicesprovide interactive analysis and delivery of corporate information to diverse user communities. Hyperion Analyzer, Spreadsheet Services, and Spreadsheet Add-in provide out-of-the-box solutions and easy-to-use personalization and visualization tools allow you to create intuitive, Web-based analysis and reporting from ERP systems, relational, multidimensional and other data sources.

Integration ServicesIntegration Servicesan optional product componentprovides a metadata-driven environment to bridge the gap between data stored in Analytic Services databases and detailed data stored in relational databases. The Hybrid Analysis feature gives business users more detail for decision-making and IT managers more modularity in designing and maintaining large-scale analytic applications. Hybrid Analysis allows portions of Analytic Services databases to be stored in a relational database. This relational stored data is mapped to the appropriate Analytic Services hierarchies. HAL (Hyperion Application Link) is an application integration and business process automation tool that allows bi-directional information exchange between transaction processing applications, desktop applications, and Hyperion Business Performance Management applications.

Application Programming Interface (API)Analytic Services APIthe developers interface to Analytic Servicesallows you to create customized applications. The API Reference provides a complete listing of API functions, platforms, and supported compilers.

Developer ProductsEssbase developer products enable the rapid creation, management and deployment of tailored enterprise analytic applicationswith or without programming knowledge. The products (for example, Application Builder, and Hyperion Objects) provide a comprehensive set of application programming interfaces, drag and drop components and services.


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Data MiningData Miningan optional product component of Analytic Servicesshows you hidden relationships and patterns in your data, enabling you to make better business decisions. Using Data Mining you can plug in various data mining algorithms, build models, and then apply them to existing Analytic Services applications and databases.

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Chapter

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Understanding Multidimensional Databases

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Essbase Analytic Services contains multidimensional databases that support analysis and management reporting applications. This chapter discusses multidimensional concepts and terminology.Note: The information in this chapter is designed for block storage databases. Some of the information is not relevant to aggregate storage databases. For detailed information on the differences between aggregate and block storage, see Chapter 57, Comparison of Aggregate and Block Storage.

This chapter contains the following topics:

OLAP and Multidimensional Databases on page 31 Dimensions and Members on page 33 Data Storage on page 44

OLAP and Multidimensional DatabasesOnline analytical processing (OLAP) is a multidimensional, multi-user, client-server computing environment for users who need to analyze enterprise data. OLAP applications span a variety of organizational functions. Finance departments use OLAP for applications such as budgeting, activity-based costing (allocations), financial performance analysis, and financial modeling. Sales departments use OLAP for sales analysis and forecasting. Among other applications, marketing departments use OLAP for market research analysis, sales forecasting, promotions analysis, customer analysis, and market/customer segmentation. Typical manufacturing OLAP applications include production planning and defect analysis.


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Important to all of the applications mentioned in the previous paragraph is the ability to provide managers with the information they need to make effective decisions about an organization's strategic directions. A successful OLAP application provides information as needed, that is, it provides just-in-time information for effective decision-making. Providing just-in-time information requires more than a base level of detailed data. Just-in-time information is computed data that usually reflects complex relationships and is often calculated on the fly. Analyzing and modeling complex relationships are practical only if response times are consistently short. In addition, because the nature of data relationships may not be known in advance, the data model must be flexible. A truly flexible data model ensures that OLAP systems can respond to changing business requirements as needed for effective decision making. Although OLAP applications are found in widely divergent functional areas, they all require the following key features:

Multidimensional views of data Calculation-intensive capabilities Time intelligence

Key to OLAP systems are multidimensional databases. Multidimensional databases not only consolidate and calculate data; they also provide retrieval and calculation of a variety of data subsets. A multidimensional database supports multiple views of data sets for users who need to analyze the relationships between data categories. For example, a marketing analyst might want answers to the following questions:

How did Product A sell last month? How does this figure compare to sales in the same month over the last five years? How did the product sell by branch, region, and territory? Did this product sell better in particular regions? Are there regional trends? Did customers return Product A last year? Were the returns due to product defects? Did the company manufacture the products in a specific plant? Did commissions and pricing affect how salespeople sold the product? Did particular salespeople do a better job of selling the product?

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Dimensions and Members

With a multidimensional database, the number of data views is limited only by the database outline, the structure that defines all elements of the database. Users can pivot the data to see information from a different viewpoint, drill down to find more detailed information, or drill up to see an overview.

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Dimensions and MembersThis section introduces the concepts of outlines, dimensions and members within a multidimensional database. If you understand dimensions and members, you are well on your way to understanding the power of a multidimensional database. A dimension represents the highest consolidation level in the database outline. The database outline presents dimensions and members in a tree structure to indicate a consolidation relationship. For example, in Figure 2, Time is a dimension and Qtr1 is a member. Analytic Services has two types of dimensions: standard dimensions and attribute dimensions. Standard dimensions represent the core components of a business plan and often relate to departmental functions. Typical standard dimensions are Time, Accounts, Product Line, Market, and Division. Dimensions change less frequently than members. Attribute dimensions are a special type of dimension that are associated with standard dimensions. Through attribute dimensions, you group and analyze members of standard dimensions based on the member attributes (characteristics). For example, you can compare the profitability of non-caffeinated products that are packaged in glass to the profitability of non-caffeinated products that are packaged in cans. Members are the individual components of a dimension. For example, Product A, Product B, and Product C might be members of the Product dimension. Each member has a unique name. A dimension can contain an unlimited number of members. Analytic Services can store the data associated with a member (referred to as a stored member in this chapter) or it can dynamically calculate the data when a user retrieves it.


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Outline HierarchiesAll Analytic Services database development begins with creating a database outline. A database outline accomplishes the following:

Defines the structural relationships between members in an Analytic Services database Organizes all the data in the database Defines the consolidations and mathematical relationships between items

Analytic Services uses the concept of members to represent data hierarchies. Each dimension consists of one or more members. The members, in turn, may consist of other members. When you create a dimension, you tell Analytic Services how to consolidate the values of its individual members. Within the tree structure of the database outline, a consolidation is a group of members in a branch of the tree. For example, many businesses summarize their data monthly, roll up the monthly data to obtain quarterly figures, and roll up the quarterly data to obtain annual figures. Businesses may also summarize data by zip code, by city, state, and country. Any dimension can be used to consolidate data for reporting purposes. In the Sample Basic database included with Analytic Server, for example, the Year dimension consists of five members: Qtr1, Qtr2, Qtr3, and Qtr4, each storing data for an individual quarter, plus Year, storing summary data for the entire year. Qtr1 consists of four members: Jan, Feb, and Mar, each storing data for an individual month, plus Qtr1, storing summary data for the entire quarter. Likewise, Qtr2, Qtr3, and Qtr4 consist of the members that represent the individual months plus the member that stores the quarterly totals. The database outline in Figure 2 uses a hierarchical structure to represent the data consolidations and relationships in Qtr1.Figure 2: Hierarchical Structure

Some dimensions consist of relatively few members, while others may have hundreds or even thousands of members. Analytic Services does not limit the number of members within a dimension and enables the addition of new members as needed.

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Dimension and Member RelationshipsAnalytic Services uses the terms defined in the following sections to describe a database outline. These terms are used throughout Analytic Services documentation. Analytic Services uses hierarchical and family history terms to describe the roles and relationships of the members in an outline. You can describe the position of the members of the branches in Figure 3 in several ways.Figure 3: Member Generation and Level Numbers

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Parents, Children, and SiblingsFigure 3 illustrates the following parent, child, and sibling relationships:

A parent is a member that has a branch below it. For example, Margin is a parent member for Sales and Cost of Goods Sold. A child is a member that has a parent above it. For example, Sales and Cost of Goods Sold are children of the parent Margin. Siblings are child members of the same immediate parent, at the same generation. For example, Sales and Cost of Goods Sold are siblings (they both have the parent Margin), but Marketing (at the same branch level) is not a sibling because its parent is Total Expenses.


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Descendants and AncestorsFigure 3 illustrates the following descendant and ancestral relationships:

Descendants are all members in branches below a parent. For example, Profit, Inventory, and Ratios are descendants of Measures. The children of Profit, Inventory, and Ratios are also descendants of Measures. Ancestors are all members in branches above a member. For example, Margin, Profit, and Measures are ancestors of Sales.

Roots and LeavesFigure 3 illustrates the following root and leaf member relationships:

The root is the top member in a branch. Measures is the root for Profit, Inventory, Ratios, and the children of Profit, Inventory, and Ratios. Leaf members have no children. They are also referred to as detail members, level 0 members, and leaf nodes. For example, Opening Inventory, Additions, and Ending Inventory are leaf members.

Generations and LevelsFigure 3 illustrates the following generations levels:

Generation refers to a consolidation level within a dimension. A root branch of the tree is generation 1. Generation numbers increase as you count from the root toward the leaf member. In Figure 3, Measures is generation 1, Profit is generation 2, and Margin is generation 3. All siblings of each level belong to the same generation; for example, both Inventory and Ratios are generation 2. Figure 4 shows part of the Product dimension with its generations numbered.Figure 4: Generations

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Level also refers to a branch within a dimension; however, levels reverse the numerical ordering that Analytic Services uses for generations. The levels count up from the leaf member toward the root. The root level number varies depending on the depth of the branch. In the example in Figure 3, Sales and Cost of Goods Sold are level 0. All other leaf members are also level 0. Margin is level 1, and Profit is level 2. Notice that the level number of Measures varies depending on the branch. For the Ratios branch, Measures is level 2. For the Total Expenses branch, Measures is level 3. Figure 5 shows part of the Product dimension with its levels numbered.Figure 5: Levels

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Generation and Level NamesTo make your reports easier to maintain, you can assign a name to a generation or level and then use the name as a shorthand for all members in that generation or level. Because changes to an outline are automatically reflected in a report, when you use generation and level names, you do not need to change the report if a member name is changed or deleted from the database outline.

Standard Dimensions and Attribute DimensionsAnalytic Services has two types of dimensions: standard dimensions and attribute dimensions. This chapter primarily considers standard dimensions because Analytic Services does not allocate storage for attribute dimension members. Instead it dynamically calculates the members when the user requests data associated with them. An attribute dimension is a special type of dimension that is associated with a standard dimension. For comprehensive discussion of attribute dimensions, see Chapter 10, Working with Attributes.


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Sparse and Dense DimensionsMost data sets of multidimensional applications have two characteristics:

Data is not smoothly and uniformly distributed. Data does not exist for the majority of member combinations. For example, all products may not be sold in all areas of the country.

Analytic Services maximizes performance by dividing the standard dimensions of an application into two types: dense dimensions and sparse dimensions. This division allows Analytic Services to cope with data that is not smoothly distributed. Analytic Services speeds up data retrieval while minimizing the memory and disk requirements. Most multidimensional databases are inherently sparse: they lack data values for the majority of member combinations. A sparse dimension is a dimension with a low percentage of available data positions filled. For example, the Sample Basic database shown in Figure 6 includes the Year, Product, Market, Measures, and Scenario dimensions. Product represents the product units, Market represents the geographical regions in which the products are sold, and Measures represents the accounts data. Because not every product is sold in every market, Market and Product are chosen as sparse dimensions. Most multidimensional databases also contain dense dimensions. A dense dimension is a dimension with a high probability that one or more data points is occupied in every combination of dimensions. For example, in the Sample Basic database, accounts data exists for almost all products in all markets, so Measures is chosen as a dense dimension. Year and Scenario are also chosen as dense dimensions. Year represents time in months, and Scenario represents whether the accounts values are budget or actual values. In Sample Basic Database Outline on page 39, Caffeinated, Intro Date, Ounces, and Pkg Type are attribute dimensions that are associated with the Product dimension. Population is an attribute dimension that is associated with the Market dimension. Members of attribute dimensions describe characteristics of the members of the dimensions with which they are associated. For example, each product has a size in ounces. Attribute dimensions are always sparse dimensions and must be associated with a sparse standard dimension. Analytic Services does

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not store the data for attribute dimensions, Analytic Services dynamically calculates the data when a user retrieves it. For a comprehensive discussion about attribute dimensions, see Chapter 10, Working with Attributes.Figure 6: Sample Basic Database Outline

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Selection of Dense and Sparse DimensionsIn most data sets, existing data tends to follow predictable patterns of density and sparsity. If you match patterns correctly, you can store the existing data in a reasonable number of fairly dense data blocks, rather than in many highly sparse data blocks. Analytic Services can make recommendations for the sparse-dense configuration of dimensions based on the following factors:

The time and accounts tags on dimensions The probable size of the data blocks Characteristics that you attribute to the dimensions in this dialog box


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You can apply a recommended configuration or you can turn off automatic configuration and manually set the sparse or dense property for each dimension. Attribute dimensions are always sparse dimensions. Keep in mind that you can associate attribute dimensions only with sparse standard dimensions.Note: The automatic configuration of dense and sparse dimensions provides only an estimate. It cannot take into account the nature of the data you will load into your database or multiple user considerations.

Dense-Sparse Configuration for Sample BasicConsider the Sample Basic database that is provided with Analytic Services. The Sample Basic database represents data for The Beverage Company (TBC). TBC does not sell every product in every market; therefore, the data set is reasonably sparse. Data values do not exist for many combinations of members in the Product and Market dimensions. For example, if Caffeine Free Cola is not sold in Florida, then data values do not exist for the combination Caffeine Free Cola (100-30)->Florida. However, consider combinations of members in the Year, Measures, and Scenario dimensions. Data values almost always exist for some member combinations on these dimensions. For example, data values exist for the member combination Sales->January->Actual because at least some products are sold in January. The sparse-dense configuration of the standard dimensions in the Sample Basic database may be summarized as follows:

The sparse standard dimension are Product and Market. The dense standard dimensions are Year, Measures, and Scenario.

Analytic Services creates a data block for each unique combination of members in the Product and Market dimensions (for more information on data blocks, see Data Storage on page 44). Each data block represents data from the dense dimensions. The data blocks are likely to have few empty cells.

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For example, consider the sparse member combination Caffeine Free Cola (100-30), New York, illustrated by Figure 7:

If accounts data (represented by the Measures dimension) exists for this combination for January, it probably exists for February and for all members in the Year dimension. If a data value exists for one member on the Measures dimension, then it is likely that other accounts data values exist for other members in the Measures dimension. If Actual accounts data values exist, then it is likely that Budget accounts data values exist.Figure 7: Dense Data Block for Sample Basic Database

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Dense and Sparse Selection ScenarioConsider a database with four standard dimensions: Time, Accounts, Region, and Product. In the following example, Time and Accounts are dense dimensions, and Region and Product are sparse dimensions.


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The two-dimensional data blocks shown in Figure 8 represent data values from the dense dimensions: Time and Accounts. The members in the Time dimension are J, F, M, and Q1. The members in the Accounts dimension are Rev, Exp, and Net.Figure 8: Two-dimensional Data Block for Time and Accounts

Analytic Services creates data blocks for combinations of members in the sparse standard dimensions (providing at least one data value exists for the member combination). The sparse dimensions are Region and Product. The members of the Region dimension are East, West, South, and Total US. The members in the Product dimension are Product A, Product B, Product C, and Total Product. Figure 9 shows 11 data blocks. No data values exist for Product A in the West and South, for Product B in the East and West, and for Product C in the East. Therefore, Analytic Services has not created data blocks for these member combinations. The data blocks that Analytic Services has created have very few empty cells.Figure 9: Data Blocks Created for Sparse Members on Region and Product

This example effectively concentrates all the sparseness into the index and concentrates all the data into fully utilized blocks. This configuration provides efficient data storage and retrieval.

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Now consider a reversal of the dense and sparse dimension selections. In the following example, Region and Product are dense dimensions, and Time and Accounts are sparse dimensions. As shown in Figure 10, the two-dimensional data blocks represent data values from the dense dimensions: Region and Product.Figure 10: Two-Dimensional Data Block for Region and Product

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Analytic Services creates data blocks for combinations of members in the sparse standard dimensions (providing at least one data value exists for the member combination). The sparse standard dimensions are Time and Accounts. Figure 11 shows 12 data blocks. Data values exist for all combinations of members in the Time and Accounts dimensions; therefore, Analytic Services creates data blocks for all the member combinations. Because data values do not exist for all products in all regions, the data blocks have many empty cells. Data blocks with many empty cells store data inefficiently.Figure 11: Data Blocks Created for Sparse Members on Time and Accounts


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Data StorageThis topic describes how data is stored in a multidimensional database. Each data value is stored in a single cell in the database. You refer to a particular data value by specifying its coordinates along each standard dimension.Note: Analytic Services does not store data for attribute dimensions. Analytic Services dynamically calculates attribute dimension data when a user retrieves the data.

Consider the simplified database shown in Figure 12.Figure 12: A Multidimensional Database Outline

This database has three dimensions: Accounts, Time, and Scenario:

The Accounts dimension has four members: Sales, COGS, Margin, and Margin%. The Time dimension has four quarter members, and Qtr1 has three month membersNote: Figure 13 shows only Qtr1 and its members.

The Scenario dimension has two child members: Budget for budget values and Actual for actual values.

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Data Storage

Data ValuesThe intersection of one member from one dimension with one member from each of the other dimensions represents a data value. The example in Figure 13 has three dimensions; thus, the dimensions and data values in the database can be represented in a cube.Figure 13: Three-Dimensional Database

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The shaded cells in Figure 14 illustrate that when you specify Sales, you are specifying the portion of the database containing eight Sales values.Figure 14: Sales Slice of the Database

Slicing a database amounts to fixing one or more dimensions at a constant value while allowing the other dimensions to vary.


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When you specify Actual Sales, you are specifying the four Sales values where Actual and Sales intersect as shown by the shaded area in Figure 15.Figure 15: Actual, Sales Slice of the Database

A data value is stored in a single cell in the database. To refer to a specific data value in a multidimensional database, you specify its member on each dimension. In Figure 16, the cell containing the data value for Sales, Jan, Actual is shaded. The data value can also be expressed using the cross-dimensional operator (->) as Sales -> Actual -> Jan.Figure 16: Sales -> Jan -> Actual Slice of the Database

Data Blocks and the Index SystemAnalytic Services uses two types of internal structures to store and access data: data blocks and the index system. Analytic Services creates a data block for each unique combination of sparse standard dimension members (providing that at least one data value exists for the sparse dimension member combination). The data block represents all the dense dimension members for its combination of sparse dimension members.

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Data Storage

Analytic Services creates an index entry for each data block. The index represents the combinations of sparse standard dimension members. It contains an entry for each unique combination of sparse standard dimension members for which at least one data value exists. For example, in the Sample Basic database outline shown in Figure 17, Product and Market are sparse dimensions.Figure 17: Product and Market Dimensions from the Sample Basic Database

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If data exists for Caffeine Free Cola in New York, then Analytic Services creates a data block and an index entry for the sparse member combination of Caffeine Free Cola (100-30) -> New York. If Caffeine Free Cola is not sold in Florida, then Analytic Services does not create a data block or an index entry for the sparse member combination of Caffeine Free Cola (100-30) -> Florida. The data block Caffeine Free Cola (100-30) -> New York represents all the Year, Measures, and Scenario dimensions for Caffeine Free Cola (100-30) -> New York. Each unique data value can be considered to exist in a cell in a data block. When Analytic Services searches for a data value, it uses the index to locate the appropriate data block.Then, within the data block, it locates the cell containing the data value. The index entry provides a pointer to the data block. The index handles sparse data efficiently because it includes only pointers to existing data blocks.


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Figure 18 shows part of a data block for the Sample Basic database. Each dimension of the block represents a dense dimension in the Sample Basic database: Time, Measures, and Scenario. A data block exists for each unique combination of members of the Product and Market sparse dimensions (providing that at least one data value exists for the combination).Figure 18: Part of a Data Block for the Sample Basic Database

Each data block is a multidimensional array that contains a fixed, ordered location for each possible combination of dense dimension members. Accessing a cell in the block does not involve sequential or index searches. The search is almost instantaneous, resulting in optimal retrieval and calculation speed. Analytic Services orders the cells in a data block according to the order of the members in the dense dimensions of the database outline.A (Dense) a1 a2 B (Dense) b1 b11 b12 b2 b21 b22 C (Dense) c1 c2 c3

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Data Storage

D (Sparse) d1 d2 d21 d22 E (Sparse) e1 e2 e3

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Th

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