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Data Manager Business Intelligence Solutions

Data Manager

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Data Manager . Business Intelligence Solutions. Data Mart and Data Warehouse Data Warehouse Architecture Dimensional Data Structure Extract, transform and load (ETL) Extract Transform Load. OLTP. OLTP. DATA MART. DATA. DATA. +/-. ERP. TEXT. x/y. F(x). F(x). - PowerPoint PPT Presentation

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Page 1: Data Manager

Data Manager

Business Intelligence Solutions

Page 2: Data Manager

Data Mart and Data Warehouse

Data Warehouse Architecture

Dimensional Data Structure

Extract, transform and load (ETL) Extract Transform Load

OLTP

ERP

OLTP

TEXT

DATA DATA

x/y +/-

F(x) F(x)

DATAMART

Page 3: Data Manager

IBM Cognos Data Manager– Extract operational data from multiple sources (both relational and non-

relational)– Merges and transforms the data to facilitate enterprise-wide reporting,

analysis, and performance management– Delivers the transformed data to coordinated data marts that make up the data warehouse– Can create metadata for use with Cognos 8 BI tools such as Query Studio and Analysis Studio and also can be easily deployed and scheduled using Cognos BI.

Page 4: Data Manager

Key Features1. Automated tasks and processes Data Manager automates many of the complex process associated with data mart

dimension and fact table creation and management, without the need for manual coding. Surrogate key management for dimension and fact tables Data Manager can generate the surrogate key for the fact table using the business key.

surrogate key

business key

Page 5: Data Manager

Surrogate key of the dimension table can be defined during the dimension build.

set up surrogate key in dimension build

Page 6: Data Manager

Support for slowly changing dimensions(SCD) Example of the SCD implementation from Granite dimension build:

Page 7: Data Manager

Late arriving Fact and Unmatched members .

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Hierarchy definitions and implementations A hierarchy is a particular view of a business dimension which organizes the structure data into levels

that represent parent-child relationships. Each hierarchy can have as many levels as you require.

Provide easy interface for processing ragged, unbalanced and recursive hierarchies– Unbalanced hierarchies have leaf nodes at more than one level with the parent of every member

coming from the level immediately above.

Balance an unbalanced hierarchies

YEAR QUARTER MONTH DAY

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– Ragged hierarchies contain members that have parents at a level higher than the immediate parent level

Example of a ragged hierarchy

– Parent-Child Relationships – Recursive Hierarchies

Example of Create recursive recursive hierarchies using hierarchies data manager

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Customized Refresh strategies in the Fact build

Example of customized refresh types in a fact build

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2. Referential integrity validation Data Manager reference explorer validates hierarchies within dimensions such as parent child relationships, multiple parents and foster children, so issues can be resolved before data is loaded into the warehouse.

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3. Scalable Architecture Data Manager dimensional ETL provides flexible and responsive capabilities. An innovative dimensional reference model allows the coordination and management of data marts of all shapes and sizes and across many different platforms.

Data Manager can use multiple processors, one processor for each job. Example of jobstream with parallel jobs.

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4. Crafting an event process– A JobStream can multi-task events and allow commands to be executed in a parallel or serial manner.

Example of a JobStream in a serial manner

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The developed JobStream can be published as Data Movement tasks into the IBM Cognos BI production environment, where they can be added to jobs and be scheduled for execution.

Example of publishJobStream as Data Movementtask

Schedule a jobin Cognos

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5. Easy deployment Data Manager provides the ability to package components and easily move them from environment to environment and test functions and scripts as they are developed in the same environment.

Page 16: Data Manager

Q & A