MicroStrategy Interview Questions revisitedRecently I had to revist the 101 MicroStrategy Interview Question bank and I realized that there were a lot of repeated questions, not so useful question, etc. I scrubbed the questions and here is new improved set. Remember: these are with prospective of an Interviewer. If you have your won question bank and wish to publish, comment here. I’ll contact you. Full credit given. 

Warehouse

1. What is fact constellation schema?2. What is star schema?3. What is snowflake schema?4. What is a surrogate key?

Surrogate key is a unique identification key, it is like an artificial or alternative key to production key, bz

the production key may be alphanumeric or composite key but the surrogate key is always single

numeric key. Assume the production key is an alphanumeric field if you create an index for this fields it

will occupy more space, so it is not advisable to join/index, bz generally all the datawarehousing fact

table are having historical data . These factable are linked with so many dimension table. if it's a

numerical fields the performance is high

5. Why do we use a staging area?6. Why do we need a DW?7. How much history should we have in a DW?8. What are the most important tables in a DW?9. Why Kimball? Why not Inmon? Or vice versa?10. Performance with a relational based query vs dimensional?11. What schema is used in your project? Why?12. What are conformed dimensions?

General Knowledge (Applies to all roles)

1. What is metadata?2. What is two-tier connection?3. What is three-tier connection?4. What is difference between 2, 3 and 4 tier connections?5. How do you achieve schema object version control (similar to VSS)?6. What are different kinds of objects in MicroStrategy?7. What’s fact table?8. Where is Administrator’s password stored? Is it stored in encrypted?9. Why do we use dimensional modeling in DW? Why not Relational?10. What is a batch?11. Differences between ROLAP, MOLAP and HOLAP?12. What is ETL?13. What types of DW’s are most common?

14. How many MSTR projects have you worked?15. What are the types of MSTR objects available?16. Explain the step-by-step technical approach after you get the Requirements from the

Client.17. What’s a System call error? Have you seen Object variable error?18. Have you ever manually edited the metadata? why?

Architect

1. Should you have DATE as ID attribute form?2. What is compound key?3. What is a fact and an attribute?4. What are Factless facts?5. What are Transformations? Is there any transformations implemented in your project?6. Explain Fact Structure(types, one by one)7. Explain Level Extension. How it is used in your project?8. Explain Fact Relation.9. Explain Fact Degradation.10. What is Compound Key Attribute? Give example from your project.11. Can you update a table in Warehouse using MicroStrategy?12. How will you resolve an issue when (by chance) an aggregate table at higher level has a

higher LTS than an aggregate table at lower level?13. What happens if LTS is high for a higher level table?14. What are the criteria used by the MicroStrategy SQL Engine to build the join tree of a

report’s SQL?15. Can MicroStrategy logical primary keys and the true (warehouse) primary keys differ?16. Oracle has a pseudo column named ROWID which is not “directly” exposed to front-end?

Can this table be used in MicroStrategy? Why one would do that?17. Can you create Schema objects in 2 tier connection? Is it recommended?

Reporting

1. What is the difference between RW document and HTML document?2. What’s smart metric?3. What is a bridge/relationship table?4. How will you resolve double counting in M-M relationship between two attributes?5. What is a CUBE?6. What are differences between View Filter and Report Filter?7. What are the different types of Filters available? Explain each with example.8. What is derived metrics? Explain the example from your project.9. What are Prompted Filters or cascaded prompts?10. How will you customize the display for Null Values?11. Can you enable/disable the thresholds based on some condition/prompt answers?12. In a Document, there are 5 reports and 5 out of them need to have a prompt so that 10

user can select first day of the week for which user want to execute the report. How many prompts would be required to be made?

13. What’s XML Cache?

14. What’s a Bulk export report?15. Can you have a prompt in free form SQL report?16. What will happen when the network connection between the webserver and one of the

clustered I-server is lost? Will report run smoothly?17. Can you prioritize report execution?

Problems :

Row number as AttributeThis is the statement that one can used to generate the row number as an attribute to be placed as the leftmost column on the grid.

ApplySimple(“row_number() OVER (ORDER BY #0 ASC)”, [ID COLUMN of Fact Table with maximum number of Rows])

Above statement would work for a DB2 warehouse. One need to change the statement for respective warehouse

Installation problem in serversIn few version like Windows 2003, Vista; installation may stuck due to firewall issue or security issues.

How to resolve this? This issue may appear because of the 3rd party utilities.

Steps:

1)       Install manually all the 3rd party installation under MSTR setup package

2)      Remove the 3rd party installation setups from the MSTR package (from 3rd party folder)

3)      Now install MSTR setup

4)      MSTR setup will skip the 3rd party utilities since it’s not present in the 3rd party folder.

FreeForm SQL Reports

A while ago I had the opportunity to prepare a short training on the FreeForm SQL reports for some of my colleagues. I thought I’d better share this with you as well, so… here is a not-at-all-exhaustive list of things worth knowing about this type of report.

What is a FF SQL?

FreeForm SQL (aka FreeStyle SQL) is a type of report which allows the designer to define its own SQL code. Notice this is a rather different approach than what we are normally used to in MicroStrategy, where we would usually let the SQL Engine do the job.

When should it be used?

1. Whenever you tried everything (VLDB properties, Metric Levels, Attribute Relationships, Table Logical Size, Data Model changes…) and the SQL Engine still doesn’t perform that join the way you want it to.

2. Whenever you want to use a data source which does not exist in the Warehouse Catalog. That’s right, with FF SQL you can use almost any data source, including those tables you see in the left hand side of the Catalog.

How do I recognize it?

You don’t, at least not from the outside. You can either edit a report and see if you can spot the unnoticeable “Freeform SQL Definition” button, or you can right click on the report and make a component search. If it has no components, you found it.

So, unless you set up some naming convention for FF SQL reports you will very soon lose track of them.

How is it created?

Click on “New -> Report” and select “Freeform SQL” from the list (you need a special role to see this option).

Type your code in the upper right hand side frame.

Now you have to map the items from the “Select” section of your script to virtual Attributes and Metrics. To do this, right click on the lower frame and select either “Add new Attribute form” or “Add new Metric”.

For a script like “SELECT country_id, country_name, SUM(sales)…” the mapping should be defined as:

These are virtual objects. You may actually have a “Country” Attribute in your project, but please don’t make the mistake of thinking these two are the same thing.

Click OK and you are back on familiar grounds.

Prompts in FF SQL

You can either create or insert them into a WHERE clause, by using the two dedicated buttons. The Prompts will show in bold pink.

Now, here is the interesting part. Let’s say you want to make some changes to the script, and you copy it into an external editor. You will notice that the prompts were converted into object IDs. Now, paste the text back into the FF SQL editor. They are bold pink again. Too bad the report won’t work anymore…

The prompts will have to be inserted again, the “button” way, if you want the report to run properly.

Words of caution.

Being what I call a “manually defined object”, the FF SQL is not subjected to automatic Schema updates. That is to say, you won’t be warned if you delete a table which is being used by such a report. So please bear in mind that maintenance for FF SQL can be harsh.

Metric Aliases

This is a little “don’t” that I stumbled upon recently.

Don’t create metric aliases that contain operators such as “-“, “+”, and so long. Although MicroStrategy allows you to do so, the database application (Oracle, Teradata,…) will nag you about expecting “something between – and ,” and of course, the report will stop executing.

Complex graph in Dashboard creation in WEBComplex graph like ‘combination: Dual Axis – Bar – line’ graph cannot be created in Dashboard in WEB.

To achieve the same, create a report in desktop and make as above mentioned graph and save.

In WEB, while creating dashboard, add this data set in dashboard by ‘right click’ data set and add with formatting option. Now the graph which cannot be done in web, can be done in this way.

Manual MappingIn a previous post, I’ve warned about the not so automatically behavior of the automatic mapping. However, I can’t blame the manual mapping for the same degree of inconsistency. I mean, boy, that’s as manual as it gets!

Take a manually mapped attribute and have a look at its source tables. Now drop the attribute from one of these tables (on database and Catalog level) and try to run a report which used that table.

On the one hand, MicroStrategy knows from the attribute definition that it can include that table into the SQL. On the other hand, it should know from the table definition, as updated in the Warehouse Catalog, that the column is no longer there, but such a small detail doesn’t have enough force to deter the SQL Engine. So it simply writes the SQL as if nothing had happened, and the only error you get is from the database (i.e. a11.attribute_id does not exist).

So, if you aren’t doing this already, don’t forget to inform the manually mapped attribute that one of its source tables decided to discontinue their relationship, next time you indulge in such data model changes.

What’s new in Microstrategy Dashboard ?Introduction: The designer can create more flexible data presentations with dashboards than with documents, since more users can be served with a single dashboard. Each user can interact with the dashboard to display only the subset of data they are interested in (using panels and selectors) or only specific attribute elements or metrics (using a selector)

What is a dashboard?A dashboard is a display of related sets of data on one screen. A dashboard is commonly used to assess company or personal performance work or work group contributions to overall goals of the business. Dashboards summarize key business indicators by presenting them in visually intuitive, easy-to-read, interactive documents.

Provides interactive functionality so users can change how they see the data. Used online rather than printed out.

While Designing Dashboard , you can choose selectors, widgets, panels, and other controls, to create a personalized, custom dashboard that suits your user’s specific needs. Various formatting options such as gradient colors and 3D effects also help you create dashboards with a style appropriate for the boardroom.

Adding interactivity to dashboards:A key aspect of a dashboard is the interactivity it allows. Interactivity lets analysts dynamically change the data displayed in Grid/Graphs or change other objects on the dashboard.

Button bar Analyzing ranges of time: Slider Analysis at a glance: Gauges, thermometers, cylinders, funnels

Gauges

Thermometer

Organizing interactivity features on a dashboardThe result of a user’s interactive selections can affect multiple objects simultaneously. You can design this using a panel stack, which is a collection of panels, each of which can contain groups of objects. Panels help you display only those groups of data that should be seen at the same time.Additional features let the user navigate between panels, and quickly change the display of data within a panel.

Panels and panel stacksText field, line, rectangle, image, panel, panel stack, selector, or Grid/Graph object are controls and grouped together put into a place holder is called panel.A panel stack is a collection of individual panels, stacked on top of each other. Example of Panel Stackpanel stack to provide the Corporate, Regional, and Detail Data “views.” Each view is an individual panel in the panel stack.

SelectorsA selector can be displayed as a button bar, a drop-down list, radio buttons and much more..

Title barsA title bar is simply an area across the top of a panel stack or Grid/Graph.

The title identifies the panel, panel stack, or Grid/Graph. The buttons allow users to minimize and maximize Grid/Graphs in MicroStrategy Web.

Quick switchQuick switch is a button that allows an analyst to quickly change a Grid/Graph from Graph view to Grid view and back, with a single click.

WidgetsA widget is a type of Report Services control that presents data in a visual and interactive way. You can think of widgets as interactive Flash-only graphs that dynamically update when you select a new set of data to view. The dashboard user can even interact with some types of widgets to manually select a set of data to analyze. A variety of widget types, such as Gauge, Heat Map, and Stacked Area widgets, are available for use in MicroStrategy dashboards.

Graph styles for dashboards•Gauge •Funnel •Area •Vertical stacked bar •Combination: Line and horizontal bar •Bubble •Pie

Important points to be consider in the interactive dashboards:

Layering data on dashboards: Panels & Panel Stacks Providing interactivity to users: selectors Enabling Grid/Graphs to control other Grid/Graphs Providing Flash analysis and interactivity: widgets Enabling transition animations in Flash Adding title bars to Grid/Graphs Quick switch for Grid/Graphs Drilling in documents

Layering multiple dashboards in a single document

It is similar to having tabs created in one web page. It used call Page Bys in the earlier versions of Microstrategy like having Corporate level , Regional level ..

Defining a selector

DHTML style Selectors

Flash Style is how the selector is displayed in Flash Mode in MicroStrategy Web

Automatic: Default DHTML type even in the flash style Fish Eye Selector: An interactive style of selector that is displayed only in Flash Mode. It

magnifies an item when a user hovers the cursor over it. This style of selector is useful because it allows a user to choose from a large list of elements without having to see all of the elements displayed at once

Action Type determines whether the selector displays elements, metrics, or panels.

In non-Flash modes in MicroStrategy Web, a Fish Eye Selector can display as a Grid/Graph (if it was created as a widget) or as a standard selector such as a listbox or button bar (if it was created as a selector).Selector items of a Fish Eye Selector with images instead of Names.

Design View

Understanding and working with widgets:

Bubble Grid: Bubbles of different colors and sizes representing the values of two metrics.

Cylinder: A simple status indicator that displays a vertical cylinder with fluid in it. The level of the fluid within the cylinder is a visual representation of a single metric value.

Data Cloud: A list of attribute elements displayed in various sizes to depict the differences in metric values between the elements.

Fish Eye Selector: An interactive selector that magnifies an item when you hover the cursor over it. It allows a user to choose from a list of attribute elements, metrics, or images without having to see all of the elements, metrics, or images displayed at once.

Funnel: A variation of a stacked bar chart that displays data that adds up to 100%. It allows a user to visualize the percent contribution of a metric to the whole.

Gauge: A simple status indicator that displays a needle that moves within a range of numbers displayed on its outside edges.

Graph Matrix: A group of area graphs that display actual values and line graphs that display forecasted values. It allows a user to quickly analyze various trends across several metric dimensions.

Heat Map: A combination of colored rectangles, each representing an attribute element, that allow you to quickly grasp the state and impact of a large number of variables at once.

Interactive Bubble Graph: A conventional bubble plot that allows you to visualize the trends of three different metrics for a set of attribute elements.

Microcharts widget :The Microcharts widget consists of compact representations of

data that allow analysts to quickly visualize trends in data.

Mainly lot of the issues had been fixed & introduced easy way handle interactive dashboards. Previous versions we used create & configure using SDKs now it gives very powerful interactive dashboard.

Please feel free to ask me any questions you may have to explain.

Logical views with MicroStrategyBusiness intelligence architects have always relied on the Datawarehouse team to create database views or perform datawarehouse changes in order to construct the BI architecture.   If something was not architected as desired, then the BI developers were forced to request these changes, and then wait for their completion before moving forward.   Since MicroStrategy 8, BI developers have had the ability to create logical tables and table aliases to circumvent this process.  This article will go through various examples on how this can be used on an implementation.

Lookup Tables and Reuse of Dimensions – The most obvious reason for requiring logical tables or aliases is for the creation of lookup tables or reuse of dimension tables.   First off, the difference between an alias and a logical table is that an alias is an exact copy of a dimension table, and if the dimension table or alias changes then both will change.   The logical table on the other hand is a custom SQL statement that utilizes any table available to the BI developer.    Lets say we have a fact table F_FACT, that stores 3 products per transaction, but the data model only has one D_PRODUCT table.    Aliasing allows us to alias D_PRODUCT into D_PRODUCT_1, D_PRODUCT_2, and D_PRODUCT_3, so that we now have 3 separate tables to join to F_FACT.   Now, lets say that the 1st product is a laptop, the 2nd product is a battery, and the 3rd product is an AC Adapter.  We could still join F_FACT to the 3 aliased product dims, but we also want only laptops to show up in D_PRODUCT_1, only batteries in D_PRODUCT_2, and only AC Adapters in D_PRODUCT_3.   This is where logical tables can come in to play.   First, lets create a logical table called D_PRODUCT_LAPTOPS which we create with the following SQL statement, ‘SELECT * from D_PRODUCT where PRODUCT_TYPE = “LAPTOP” ‘.    Quite simply, we have created our own dimension table of laptop products without additional support from the EDW team.

Case Study:  Using Logical Views to make a Fact table from a Dimension - Lets say we have a dimension table called D_EMPLOYEE with the fields employee_key, employee_id, employee_name, record_start_date, record_end_date, employee_start_date, employee_end_date, and organization.

Now, lets say we want to be able to count Active and Terminated employees from a fact.  Our first problem is that D_EMPLOYEE is a type 2 dimension, so we need to pull only the

latest record on this dimension.   For the metric, we have the option of building the count of active and terminated employees either on the fact table or by building a fact object in MicroStrategy.  For this demonstration, we will build the counts on the fact itself.

In order to pull the latest record from D_EMPLOYEE, we will use the following WHERE condition:WHERE RECORD_END_DATE = ‘12/31/9999′ or RECORD_END_DATE = EMPLOYEE_END_DATE which will pull the latest record for each employee.

For the facts, we will add the following fields to the SELECT part of the query: CASE WHEN RECORD_END_DATE = ‘12/31/9999′  THEN  1 ELSE 0 END as ACTIVE AND  CASE WHEN EMPLOYEE_END_DATE is not null THEN  1 ELSE 0 END as TERMINATED.

The Final Logical table will look as follows, and now we have a new fact table.

Case Study:  The POOL technique – Once you start to use Logical table , you will start to see that this can be a very powerful tool that can accomplish a great deal, as long as performance allows it.   Please note that these table Views just serve as queries on the database, and are not materialized in anyway.   What I often do after creating a complicated logical view is run it through a query tool like Toad.   If it does not return results immediately, then I send the query off to our DBA to see what they can do.

The POOL technique (which I’ve named it) is actually a technique for developing complex SQL reports when there are no data warehouses or BI Tools.  The point here is that you can use this technique to develop a complex piece of SQL, and then use that SQL in a MicroStrategy logical view, so you can build metrics and attributes on top of that SQL.   This technique is also great for developing Freefrom SQL queries in MicroStrategy.

The concept is simple.  First develop a query that gets you as far as you can with the base tables, and then use that query as the base table for a new query.   Repeat until you have what you need.  One other point is to try to avoid Sub Selects as much as possible because they can seriously slow down performance.

Lets use the table D_EMPLOYEE above and the logical view F_EMPLOYEE as our basis.  The report we want to create is a list of active employees, their current organization, and the number of organizations they’ve been in.  If the number of organizations is greater than 5 then we want to mark this record as a MOVER.

First, we build SQL to get as far as we can.  I don’t put the number of Organizations in this query for illustrative purposes, but do you see how to calculate number of Organizations in this query without a sub Select?

Next we use the statement just created as the base table for the next select, and name this base table POOL.  We then create a query based on POOL which now calculates the Number of Organizations.

Now we use the SQL statement above for our base table, and call that table POOL2.   We do this to add the MOVER field to the report.

We can keep going if we had more complex requirements, but the point is that this technique can be used to develop complex queries, which we can then plop into a MicroStrategy logical tables.   Maybe we will create an attribute called MOVER?   The options are now far greater with logical tables.

Star Schema vs. Snow Flake for MicroStrategyFri, 2009-07-24 17:38 

database

 

MicroStrategy Architect

 

Many have questions on which one is better and why or what best fits with MSTR, a Star Schema or a Snow flake?

 

I would say snowflake is better for analytical reasons. But technically speaking, both of them have their own pros and cons.

 

Star Schema: In a typical star schema, all the dimensional tables are related through a fact table. There is not direct relation between dimension tables. An example of such design follows, we can considering a very small scenario with region hierarchy, so only few columns are included in the fact table or dimension tables.

 

Country_Dim has country_id and Country_desc (only two columns, may be the default columns like created date or so)

 

State_Dim has state_id and state_desc (similar to country_dim, this table has two columns)

 

Revenue_fact has country_id, state_id an few facts like amt, sales and so on.

 

In this design there is no direct relation between the two dimensions and the relation between them is defined in the fact table (having both the keys).

 

On the other hand,

Snowflake Schema: In a snow flake design, there will be a direct relation between the dimension tables. Considering the same example as above, the design of a region hierarchy would be some thing as below.

 

Country_Dim has country_id and Country_desc (only two columns, may be the default coulmns like created date or so)

 

State_Dim has state_id, state_desc and country_id 

 

Revenue_fact has state_id an few facts like amt, sales and so on.

 

In this design, country_id is the foreign in the state table, this makes a relation between the dim tables and there is no country_id in the fact table.

 

This discuss of which is better bring up many points and there are always many pros and cons for both the structures, like.. based on the above design or example, country with a fact can be retrieved from directly joining the country_dim with the fact table, one join is eliminated (on state_dim). But the other thing which is not great about star schema is that is occupies more space than the snow flake as it has many columns than the Snow flake design.

 

Keeping all these in mind, I would say snow flake would be better for MicroStrategy, as in snowflake, relation between the dimension tables exists which allows a MicroStrategy architect to design the attributes with relations. These relation help in default drilling and ad-hoc reporting. MicroStrategy being an analytical tool, I would think both these properties would give flexibility to the end-user and are important for analysis.

Security Filter vs. Security Role

Security Filter vs. Security Role

When I initially started playing on this tool, it was always confusing for me between Security Filters and Security Roles. I will briefly describe the difference between those two.

Security Filter: A filter applied in the report (reflects in the where clause of the SQL) and can be associated to a user or a group per project. If a Security filter is linked to a user, this reflects in the where clause of any report the user executes (might be ad-hoc or canned). 

Security Role: In simple words, it is grouping of privileges. Like if a user can "execute a report", "create new report", "drilling option" and so on. A Security Role can be linked to a User or group. 

Security Role is nothing to do with the data. It is designed to provide privileges based on who is logging in, on the other hand Security Filter is restricting the data.

New Features in MicroStrategy Intelligence Server 9.3Fri, 2012-09-21 04:38

  Configurable formatting for table of contents Customization of Report service Document's table of contents by formatting such as font properties, title alignment, indentation and borders, the report look and feel can be improved. Dashboards enhancements  Display forms and sort on selector: The elements in the report can be sorted in a desired manner so that the user can choose a flexible sorting option from multiple forms, before building a report.  Drilling across templates: Drilling on one Grid/graph to simultaneous drilling can be done on another  Grid/graph.  Export a single report in a dashboard: The user can choose to export the grid/graph on the dashboard instead of exporting the entire dashboard as a PDF/Microsoft excel.  Search Box selector: In this new style selector as we type in the search box  for an element  it shows the matching list of elements so the user can select among the displayed list of elements.  Filter Panel: This type of panel stack contains only selectors, which users interact with to filter the data displayed in a dashboard.   Widget support:

  Network Visualization widget: This widget displays on web. It displays different colors/line between Map markers depending on Metric values.  Image Layout widget: Displays an image overlaid with colored areas or bubble markers. Displayed in web as well as be used on applications for Microstrategy Mobile for ipad.  Mash up widget: This widget, previously available through the MicroStrategy SDK, is now available out of the box to    support its use in Visual Insight analyses and MicroStrategy Web.  Density maps with MicroStrategy Mobile and the Map widget : Designers can define the Map widget for MicroStrategy Mobile for iPhone and  iPad to display shades of color to indicate the concentration of locations on the map.  The following widget enhancements can now be used on applications for MicroStrategy Mobile for Android  Micro charts widget: Consists of compact representations of data that allow analysts to quickly visualize trends in data. Visual Insight  Enhanced mapping options: New map visualizations include Density Maps and Image Layouts. Additionally, maps can be created by using latitude and longitude as attribute forms of a single attribute.  New Visualization support: Visual Insight has been enhanced to include support for the following visualizations.   Network Visualization: Displays lines between map markers, which can have different line thickness or colors depending on metric values.  Density Map Visualization: Displays data on an interactive map as areas color-coded based on the population density of locations on the map.  Graph Matrix Visualization: Includes several area graphs that display current values, each with a corresponding line graph above to show forecasted values.  Image Layout Visualization: Displays an image overlaid with colored areas or bubble markers.  Graph Matrix Visualization: This visualization has been enhanced as follows:·         New formatting options are available, such as applying banding and showing or hiding grid lines.·         A new graph element shape, the tick, has been added, which can help users more easily distinguish different data points in graphs.·         A matrix of scatter graphs can be displayed.   Combined Visualizations: Multiple visualizations can be displayed at the same time. We can insert multiple visualizations as well as insert and format a text field in the same panel. Additionally, an element selected on one visualization can filter data in other visualizations.   Use multiple Datasets in a Visual Insight dashboard: Two visualizations, which are sourced from different datasets, can be displayed side-by-side. Multiple Visual Insight panels: You can add panels to a layout tab to layer data in an analysis, creating stacks of analytic layers on a single analysis page.  Multiple Visual Insight worksheets with distinct filters: You can insert multiple layouts in a Visual Insight analysis, and each layout can have its own set of filters, page-by, and visualizations.  Using actions in a visualization to update data in a separate visualization: You can filter, drill, or select data in a visualization to automatically update the data displayed in another visualization.  Derived metric support: Derived metrics can be created and used within Visual Insight. This provides capabilities such as shortcut metric options as well as user-friendly interfaces to create derived metrics.  Searching enhancements·         You can search long element lists used in attribute element selectors.  ·         A new Search Box selector is available, which is ideal for long element lists. As you type in the Search Box, a list of elements matching the search criteria is presented and an element can be selected.   Migration from imported data to the main data warehouse: The migration of data for an analysis to go from using imported data to connecting to the main data warehouse has been simplified.  Themes:    ·   Themes including Light and Dark can be applied to quickly update the formatting of the whole Analysis.    ·  The default theme preference can be set at the user level.  Exporting options: A single visualization as well as the current view of the whole analysis can be exported as an image. Additionally, individual grids and graphs can be exported to Excel or as a PDF.   Enhancements in Flash View Mode of an Analysis:     ·    Support for auto-resizing to adjust the size based on the web browser window size.    ·    Filter panel capabilities including expand, collapse, resize, element count, filter summary, and                         apply are available. 

MicroStrategy Distribution Services  Dynamic recipients list: The Dynamic recipients list allows you to select the recipients of subscriptions and personalization through the use of MicroStrategy reports. This can be used in addition to the standard support of choosing Distribution Services contacts directly as the recipients of subscriptions and personalization. MicroStrategy Transaction Services  Attribute element selections for transactions: Allows users to select the element of an attribute to submit changes to their data in a Transaction Services-enabled document.  Offline transactions: Allows iOS mobile users to submit transactions while offline. Transactions submitted while offline are put into a queue and processed automatically when a connection to the MicroStrategy Mobile Server is re-established.   Signature capture: You can provide their signature in a Transaction Services-enabled document using the Signature Capture input object control.  Format verification for transactions: Designers can specify the format in which users must enter data in a text field input object control. For example, users might be required to enter data in a phone number or zip code format. MicroStrategy Intelligence Server  Intelligent Total calculations: The Total subtotal for all metrics is calculated based on the metric’s function, rather than always defaulting to a simple summation. In addition, totals for derived metrics can also be calculated from the base level data available in a report. This is particularly useful for derived metrics such as distinct counts and averages.  Parallel SQL Execution: Independent passes of a multi-pass SQL can be processed in parallel to improve overall reporting execution time. This new option is particularly useful for reports that source data from multiple sources, including reports that source data from both relational and MDX cube sources.  Communication encryption: Communications between MicroStrategy Desktop and MicroStrategy Intelligence Server are encrypted to provide enhanced security.  Health Center configuration: Configuration of Health Agents and Master Health Agents is fully integrated into the MicroStrategy Configuration Wizard.   Intelligence Server SSL configuration:o    The Configuration Wizard supports configuration of SSL for Intelligence Server.o    The MicroStrategy Service Manager can be used to update the SSL port number.  Support for Open Office Calc: Output exported to Microsoft Excel 2007 or higher can be opened with Open Office Calc.   Currency internationalization: The International Currency Symbol ¤ is translated into an actual currency symbol based on the user’s choice of language for Number and Date formatting.   Enhanced History List storage and retrieval with database and file support: You can now store History List messages as a combination of a file on your Intelligence Server machine and a repository on a database. By storing History List messages using the combination of these techniques, the History List system can achieve faster response times for both the creation and retrieval of History List messages.  New database platform support for MicroStrategy 9.3:o    MicroStrategy supports all of the major  distributions of Hadoop through the use of the Hive infrastructure.o    Action Vectorwise 1.6 and 2.0o    Aster Data cluster 4.6.xo    Composite 6.1o    Enterprise DB Postgres Plus Advanced Server 9 and 9.1o    Exasolution 4.0o    Greenplum 4.2o    IBM DB2 UDB for z/OS 10 (DB2 UDB V9 for z/OS)o    Infobright 4.0.xo    Informatica Data Services 9.1o    Kognitio WX 7.2o    Microsoft SQL Server 2008 SP1/SP2/SP3 and 2008 R2/R2 SP1o    Microsoft SQL Server 2012o    ParAccel 3.5o    PostgreSQL 9.1o    Salesforce.como    SAP BW 7.3o    SAP HANA 1.0 SP2

o    Sybase Adaptive Server 15.7o    Sybase IQ 15.3 and 15.4o    Teradata 14.0o    Vertica 5.1 and 6.0o    MicroStrategy ODBC drivers version 6.1, including two new drivers: Salesforce.com and Microsoft SQL Server. MDX cube sources integration  Performance: Performance improvements have been implemented for reporting on large Microsoft Analysis Services data sources.  Support for dynamic metric aliases with SAP text variables: Metric aliases can be automatically populated with the results of an SAP text variable. If the name of an SAP measure contains an SAP text variable, MicroStrategy replaces that text variable with its resolved value and includes the value in the name of the metric.  Data mining support: Creating training and predictive metrics is supported when reporting on MDX cube sources. You can create training metric using models defined within MicroStrategy Data Mining Services, or you can create a predictive metric by applying PMML from an external source.

What is New in MIcroStrategy Mobile 9.3?Fri, 2012-09-21 04:17 

MicroStrategy Mobile 9.3 MicroStrategy 9.3 mainly focused on improvements in end users, developers and mobile.  The following are the places where there are changes to MicroStrategy Mobile.

1. 1. MicroStrategy Mobile for iPhone2. 2. MicroStrategy Mobile for iPad3. 3. MicroStrategy Mobile for Android4. 4. MicroStrategy Mobile for Mobile Server

  MicroStrategy Mobile for iPhone

Linking with selector values: When linking to documents, the designer can set the value of a selector in the target

document to use the current value of a selector in the source document. 

AirPlay Mirroring support: Display Visual Insight analyses on an external iPhone 4S display connected to an Apple

TV device. The below link helps us how to use iPhone in AirPlay Mirroring. http://www.youtube.com/watch?v=XfOLQPyrHM0&feature=relmfu

Data wipe: If a mobile device's security certificate is invalid, any report or document caches on the mobile device

are deleted.MicroStrategy Mobile for iPad

Cloud Personal account support: You can configure your iPad to access and view the dashboards using your

MicroStrategy Cloud Personal account. In iPad MicroStrategy app from settings we can configure MicroStrategy

Cloud Personal ID. With this we can view any dashboards created using cloud personal. The below link will help us

how to configure cloud personal.http://www.youtube.com/watch?v=1X1Pl46k55U 

Annotations: Add annotations, such as comments and freehand drawings, to a screenshot of your dashboard, and

share the annotated screenshot with your contacts. With this version we can share and email screen shots to

contacts. The below link will show us the video how we can use annotations in iPad.http://www.youtube.com/watch?v=5FY9bCzbh1I   The below screenshot is the excatly the same screen which we share with our contacts.

 

Laser pointer during Airplay: While presenting Visual Insight analyses using an iPad and an external display, tap

and hold the analysis to display a laser pointer.http://www.youtube.com/watch?v=XfOLQPyrHM0&feature=relmfu  

AirPlay Mirroring support: Display Visual Insight analyses on an external iPad 2 display connected to an Apple TV

device. The below video will help us how to connect the iPad and how to use laser pointer during airplay. http://www.youtube.com/watch?v=XfOLQPyrHM0&feature=relmfu 

Linking with selector values: When linking to documents, the designer can set the value of a selector in the target

document to use the current value of a selector in the source document.   MicroStrategy Mobile for Android

Transaction Services support: When using an Android device, MicroStrategy Mobile can take advantage of the

following Transaction Services features:

o Attribute element selections for transactions.MicroStrategy Mobile Server 

Pre-cache loading indicator: When creating a custom home screen that displays a single report or document when

the application starts, you can choose to display a loading indicator to measure the progress for subscription

synchronization and pre-caching. The below screenshot is where we can customize the home screen and add a

pre-cache and subscription synchronization bar to the mobile device.

What’s factless factShare this:inSharedigg

I have been reading about factless fact table for quite some time and had assumption that bridge table in case of M-M relationship was “the” factless. But while having a knowledge

sharing session I was given a total new definition. That was convincing but unbelievable. Though bridge table is actually a factless fact table but not as per Kimball.

A factless fact table is table that doesn’t have fact at all. They may consist of nothing but keys. There are tow types of factless fact table. 1-> event 2-> coverage.

Take an example of a factless fact table that records an event. Many event-tracking tables in dimensional data warehouses turn out to be factless. Take an example of tracking student attendance. Imagine that you have a modern student tracking system that detects each student attendance event each day. When the student walks through the door into the lecture, a record is generated.

One can easily list the dimensions surrounding the student attendance event.Date: one record in this dimension for each day on the calendarStudent: one record in this dimension for each studentCourse: one record in this dimension for each course taught each semesterTeacher: one record in this dimension for each teacherFacility: one record in this dimension for each room, laboratory, or athletic field

The only problem is that there is no obvious fact to record each time a student attends a lecture or suits up for physical education. Tangible facts such as the grade for the course don’t belong in this fact table. This fact table represents the student attendance process, not the semester grading process or even the midterm exam process. Actually, this fact table consisting only of keys is a perfectly good fact table and probably ought to be left as is

A second kind of factless fact table is called a coverage table. Coverage tables are frequently needed when a primary fact table in a dimensional data warehouse is sparse. Take simple sales fact table that records the sales of products in stores on particular days under each promotion condition. The sales fact table does answer many interesting questions but cannot answer questions about things that didn’t happen. For instance, it cannot answer the question, “Which products were on promotion that didn’t sell?” because it contains only the records of products that did sell. The coverage table comes to the rescue. A record is placed in the coverage table for each product in each store that is on promotion in each time period. In general, which products are on promotion varies by all of the dimensions of product, store, promotion, and time. This complex many-to-many relationship must be expressed as a fact table.

The coverage table must only contain the items on promotion; the items not on promotion that also did not sell can be left out. Also, it is likely for administrative reasons that the assignment of products to promotions takes place periodically, rather than every day. Often a store manager will set up promotions in a store once each week. Thus we don’t need a record for every product every day. One record per product per promotion per store each week will do.

Answering the question, “Which products were on promotion that did not sell?” requires a two-step application. First, consult the coverage table for the list of products on promotion on that day in that store. Second, consult the sales table for the list of products that did sell. The desired answer is the set difference between these two lists of products.

Tiers in MicroStrategyShare this:inSharedigg

I have heard people saying web is three tier connection in several interview and desktop (with I-server) is a two tier connection. Such answers about tiers really gives me tears. [:)]. You are hear reading this page just mean that you are too lazy to read the MicroStrategy PDFs. Anyways here is the information about various tiers.

Anything that doesn’t requires I-server is 2 tier. One can have two tier connection not only with Access but also SQL Server, Oracle, Netizza, Teradata, etc, In fact with any damn database. In such case, Desktop and Metadata/Database are two tires. DSN is important in this case. In fact that become heart in 2 tier. You never need to use Configuration Manager in case of a 2 tier connection.

Any time you use configuration manager to connect I-Server to Metadata (obviously with DSN) is a three tier. In this case the tiers are, Desktop – I-Server – Metadata/Database.

Any time you use Web is a 4 tier architecture. And tiers are as follows.Web Browser – Web Server – I-Server – Metadata/Database.

A 5 tier architecture is also possible. There are various vendors who sell installable reporting tool based on MicroStrategy architecture. In this case the 5th tier sits between Web Browser and Server.

“Add to Percentage” metric added in brainShare this:inSharedigg

So here come the ghost of Cashier Dashboard report. Armed with not matching different table heterogeneous for date, 24 metrics.. This gave me cold shiver when I started it. Now having to complete the percentage, it was a tricky part. I added so many derived metrics. Made the report OLAP. Shouldn’t be doing that. Keep it Standard Stupid. I played with “Add to ….” is added in my brain.