Microstrategy Analytics

Evaluation order of calculations Evaluation order is the order in which objects are calculated by MicroStrategy’s Analytical Engine. Changing the order in which data is calculated can change report results. You change the evaluation order of a report’s data calculation by changing the order in which compound smart metrics, consolidations, derived metrics, derived elements, report limits, and subtotals on the report are calculated. The  default order of calculation is as follows: Compound smart metrics (which are compound metrics with smart totals enabled) Consolidations, which are evaluated by their relative position on the report template: Rows, from left to right Columns, from top to bottom Report limits Subtotals Compound metrics that are not the direct aggregations of other metrics can be used in the evaluation order by setting the  Allow Smart Metrics  option of the Metric Editor to  Yes .

Evaluation Ordering Evaluation Ordering is an advanced property that is hidden by default. For information on how to display this property, see  Viewing and changing advanced VLDB properties . An evaluation order is the order in which the MicroStrategy Analytical Engine performs different kinds of calculations during the data population stage. The Evaluation Ordering property determines the order in which calculations are resolved. MicroStrategy objects that are included in the evaluation order include consolidations, compound smart metrics, report limits, subtotals, derived metrics, and derived elements. Some result data can differ depending on the evaluation order of these objects. • 6.x order - Calculate derived metric/smart compound metric before derived elements/consolidation and all subtotals as smart : This option is used primarily to support backward compatibility. It is recommended in most scenarios to update your project to use the 9.x evaluation order described below. • ...

  The amount of data retrieved and objects being used in a Report Services Dashboard have a direct impact in the size of the final Dashboard. The bigger the Dashboard size the longer it will take to be prepared, be sent to the client, and render.   Client Rendering Once the data reaches the end user's browser window the data has to be formatted according to the definition of the Dashboard as specified in the formatting set by the architect. To do so the browser will have to either build the HTML page in DHTML mode or initialize the flash container and parse the XML.   Client rendering greatly varies depending on the hardware used. More powerful machines will render dashboard faster for a list of recommended client hardware specifications please refer to the Readme File for the specific version of MicroStrategy.   Optimization Techniques common to DHTML and Flash Client rendering time greatly relies in the amount of XML that needs to be parsed. In order to ensure that...

The Report Execution Process  Report execution process at a high level: The report execution process is a three-step process:  1. Query Stage : Retrieve data from the warehouse  2. Populate and Evaluate : Fill report data required for display  3. Cross-tab : Pivot and display sorting and page-by Each of the engines plays an important part in the report execution process.  As you can imagine, the SQL Engine performs its role during the Query stage while the Query Engine and Analytical Engine can be involved in all three stages.

Ways to create derived elements Using the Derived Elements Editor, you can create derived elements using the techniques described in the topics listed below: Grouping attribute elements to create derived elements Filtering attribute elements to create derived elements Using calculations to create derived elements

Components of the MicroStrategy Engine The MicroStrategy Engine is built on three core components that work together to process report requests efficiently: SQL Engine Query Engine Analytical Engine MicroStrategy Engine architecture overview Each engine handles a specific stage of report execution: SQL Engine: Generates optimized SQL and returns result sets for requests that can be fully resolved by SQL. Query Engine: Executes the SQL statements generated by the SQL Engine against the data source. Analytical Engine: Performs advanced calculations and processing that cannot be completed using SQL alone. Together, these components deliver fast, scalable, and accurate business intelligence reporting.

MicroStrategy Hadoop Gateway operation modes MicroStrategy Hadoop Gateway is a native connector which was built based on Spark 1.6.x. You can choose one or more data files from Hadoop HDFS and load them into MicroStrategy Intelligence Server. Data files can be published as either an In-Memory Cube or a Live Connect Cube. MicroStrategy Hadoop Gateway supports three operation modes : YARN client Standalone (HDP cluster does not support Standalone) Local YARN client mode: The driver runs in the client process, and the application master is only used for requesting resources from YARN. Running in this mode requires YARN service to be enabled on your Hadoop cluster. Standalone mode:  MicroStrategy Hadoop Gateway uses Spark Master to coordinate data processing. Local mode:  no application is deployed in the Spark nodes. All data processing is executed in the MicroStrategy Hadoop Gateway host. This modality is intended for testing and troubleshooting.

Partition Key Selection guidelines MicroStrategy The partition attribute is typically dictated by specific application needs. Below are some general guidelines for identifying a good partition attribute. Some of the largest fact tables in the application are typically good candidates for partitioning and thus influence the choice of the partition attribute.  Data should be partitioned in such a way that it allows for the most number of partitions to be involved in any question that is asked of the application. Attributes that are frequently used for filtering or selections do not make for good partition attributes. The partition attribute should allow for near uniform distribution of data across the partitions, so that the workload on each partition is evenly distributed. To support best dashboard execution and concurrency performance, MicroStrategy has chosen to limit the number of logical CPUs engaged for any single grid evaluation to  4 . Columns on which some of the larger...

Optimization standards to help developers work with the System Administrator to optimize network data transfer speeds: Place all server components in the same segment to minimize latency between the Intelligence Server, Web server, data warehouse server, and metadata server Expand bandwidth and minimize latency between servers and clients to ensure that bottlenecks do not occur when data is requested over your network Use HTTP compression between the Web servers and Web clients to achieve maximum throughput between these components Configure a Web proxy server to handle caching and reduce the load on the Web server

The logical table size calculation in Microstrategy The logical table size is an integer number that represents the granularity or level of aggregation of a particular table. It is called 'logical' because it is not related to the physical size of the tables (number of rows). It is calculated according to the attribute IDs that are present in the table and their level in the system hierarchy.   Even though, the number does not reveal the actual number of rows in the table, it is an accurate way of measuring a table size without having to access its contents.   MicroStrategy Engine utilizes an algorithm based on attribute keys to calculate the Logical Table Size (LTS):   Given the following tables:     The algorithm that calculates the table sizes performs the following steps: Calculate the number of levels per hierarchy: Hierarchy 1: 3 Hierarchy 2: 4 Calculate each attribute individual weight according to the level in the hierarchy (level in hierarchy/number of ...

Stages in MicroStrategy Report Execution Process The report execution is typically a 3 step process process of the below: Query Stage Populate & Evaluate Stage Cross-tab stage Query Stage:       Retrieve data from the warehouse  Populate & Evaluate Stage:       Fill report data for display Cross-tab Stage:      Pivot and display sorting and page-by 

Limit the number of attribute elements displayed in a prompt in MicroStrategy Follow the steps below: Right-click on the project and select 'Project Configuration.' Select the 'Advanced' tab, as shown below: Change the setting for 'Attribute element browsing' (circled in red above) to the limit that is desired for the project.   When the report is executed and the prompt resolution occurs, the display contains the following feature circled in red below:  

Order of tables appear in the SQL generated by the MicroStrategy SQL Generation Engine By default, the MicroStrategy SQL Generation Engine orders the tables in the following way( FMRL ): Fact Tables Metric Qualification (MQ) Tables Relationship Tables Lookup Tables

Microstrategy Document Editor Sections Important Notes: The Layout area is in the center of the Document Editor interface and provides the framework for precisely controlling where controls (such as text fields, grid and graph reports, images, and widgets) are displayed when the document is viewed in different display modes, printed, exported, emailed, and so on. To add data to the document, drag objects from the  Dataset Objects  panel and drop them into the  Layout  area. Controls are rendered differently depending on what section they are placed in, as described below:   Page Header : The control is displayed at the top of each page in the document. By default, if a document contains multiple layouts, the same Page Header is displayed for all layouts in the document. You can change this setting so that each layout has a separate Page Header. Document Header : The control is displayed once at the beginning of the document, immediately below the Page Header sec...

Use a Visualization to Filter the Data in Another Visualization Once you add visualizations to a dossier, you can use one visualization to filter or highlight data in another visualization. Define one visualization as the source. Then, select the other visualizations you want to filter or highlight as targets. The target visualizations only display or highlight data that also appears in the source. Your target visualization can be in any chapter or page within your dossier. Open a dossier with two or more visualizations. To enable a visualization to filter or highlight the data in another visualization Open the dossier  you want to modify. Hover over the visualization to use as the source and click  More   in the top right and choose  Select Target . A   icon appears in the upper left corner of the source visualization. The name of the source visualization appears after  Use visualization  at the top of the screen. If the source visualization...

Allow a Visualization to Update the Data in Another Visualization After adding multiple visualizations to a dossier, you can select values in one visualization (that is, the source) to automatically update data in another visualization (that is, the target). This is done by creating a filter on a visualization that targets other visualizations. To Add a Target Visualization to Your Dossier: Open the dossier with the visualization. Click  Insert Visualization   . A blank visualization appears in the dossier. From the Visualizations panel, select  Grid   . Drag an attribute from the Datasets panel to the  Rows  area of the Editor panel to add attributes to the rows. Drag an attribute from the Datasets panel to the  Columns  area of the Editor panel to add attributes to the columns. Drag a metric from the Datasets panel to the  Metrics  area of the Editor panel, to add a metric to the grid. The Metric Names attribute automatically appears i...

Create a Visualization Filter You can select attribute values to filter data that appears in a visualization by creating an attribute filter. Create a visualization filter by dragging attributes and metrics from the Datasets panel. To create an attribute filter Open the dossier  you want to modify. Select the chapter that contains the visualization to filter. Click  Filter  . An empty filter appears in the dossier. Drag the attributes and metrics for filtering from the Datasets panel to the empty filter. Use the Ctrl key to select multiple attributes and metrics. In the filter, click  Select Target . Click on target visualizations or visualization filters to select them. You can select targets across chapters and pages, as long as they are all on the same page. Click  Apply . Click  More   in the filter and select options for modifying the filter. The available options are based on the objects you select.

Customers Who Live in the Same City as Call Centers Your new utility company has call centers located throughout the country, and your recent surveys indicate that customers who live in the same city as a call center are particularly satisfied with service due to extremely rapid repairs during power outages. To begin your new advertising campaign, you want to generate a list of Call Centers that coincide with Customer Cities. The following steps create an attribute-to-attribute qualification filter that generates the list of desired cities. To Create an Attribute-To-Attribute Qualification that Compares the Call Center and Customer City Attributes In MicroStrategy Web, log in to a project. Open any folder page (for example, click Shared Folders on the home page). Click the  Create Filter  icon  . From the Object browser on the left, select the  Customer City  attribute from the Customers hierarchy and drag it to the filter pane on the right. Change  Qualify...

Custom Tooltips in Microstrategy developer and Web The following table describes the macros you can use to customize graph tooltips in both MicroStrategy Developer and MicroStrategy Web: Macro Information Displayed {&TOOLTIP} All relevant labels and values associated with a graph item. {&GROUPLABEL} Name of the graph item's category. This value is often the graph item's attribute element information, as attributes are commonly used as the categories of graph reports. {&SERIESLABEL} Name of the graph item’s series. This value is often the graph item's metric name information, as metrics are commonly used as the series of graph reports. {&VALUE} The value of a given data point. {&XVALUE} The X-value of a data point. Only applicable to Bubble charts and Scatter plots. {&YVALUE} The Y-value of a data point. Only applicable to Bubble charts and Scatter plots. {&ZVALUE} The Z-value of a data point. Only applicable to Bubble charts and Scatter plots. {...