Skip to main content

Filtering for a Level Metric


What is filtering for a level metric?
The filtering setting for a level metric governs the relationship between the report filter and the calculation of the metric. The filtering options are:
  1. Standard filtering - allows the report filter to interact as usual in the metric calculation. The metric calculates only for the elements found in the filter definition. The filter criteria for the report is found in the WHERE clause of the SQL statement which calculates the metric in question.
  2. Absolute filtering - changes the filter on descendents of the target. It raises it to the level of the target, if possible.
    • If the attribute in the metric filter is a parent of the attribute in the report filter, calculations are performed only on elements to which the report filter applies.
    • If the attribute in the metric filter is of the same level or a child of the attribute in the report filter, calculations occur as specified by the report filter. Absolute filtering influences what is displayed on the report, not its calculations. It includes the report criteria in a subquery rather than in the WHERE clause itself.
  3. Ignore filtering - omits filtering criteria based on the attribute in the target and its related attributes (parents and children). The report filter does not appear anywhere in the SQL for a metric with this setting.
  4. None - can be summarized as unspecified-the filtering behavior for the target is not determined by this component. Instead, the target and group components of this level unit define the filter.
    • If the report includes an attribute in the same hierarchy as that indicated by the metric filter, aggregation takes place at the level of that attribute.
    • If the report does not include other attributes in the same hierarchy as that indicated by the metric filter, aggregation defaults to the "Absolute" option.
How Absolute and Ignore Filtering modify the results of the report:
Take for example the following report and metric:
Report Filter: Year = 2004

Attributes: Quarter & Month

Metric: Level Profit

external image TN5700-8X-2537_1.jpg

external image TN5700-8X-2537_2.jpg

Because the Filtering is currently set to standard, then the report filter will interact with the metric calculation normally and apply the filter to the metric.
Now if the Filtering is changed to absolute, then again, nothing will change. Because the target is set at the Report Level, then the level of the target is not raised and the results remain unchanged.
However, if the Filtering is set to Ignore, then the Report Filter is ignored and additional 2003 data is displayed for the Level Profit as shown below:
external image TN5700-8X-2537_3.jpg

This is because ignore Filtering will remove any report filters that are related to the target (parent or child). Because the Target is Report Level, which is the Month & Quarter, and Year is a parent of both of those, it is removed.
For more examples regarding Level Metrics, refer to the 'Level Metrics' sectino of the Advanced Reporting Guide.

Comments

Popular posts from this blog

Fact tables levels tables in Microstrategy explained

Fact tables levels in Microstrategy: Fact tables are used to store fact data. Fact tables should contain attribute Id's and fact values which are measurable. All the descriptive information about the fact tables should stored in Dimension tables either in Star Schema fashion or Snow Flake Schema fashion which is best suited to your reporting solution. Since attributes provide context for fact values, both fact columns and attribute ID columns are included in fact tables. Facts help to link indirectly related attributes using these attribute ID columns. The attribute ID columns included in a fact table represent the level at which the facts in that table are stored. So the level of a fact table in the Fact_Item_Day_Customer can be the attribute Id's which is at Day, Item & Customer Id level. For example, fact tables containing sales and inventory data look like the tables shown in the following diagram: Base fact columns ver...

Case functions Microstrategy

Ca se functions Microstrategy Case functions return specified data in a SQL query based on the evaluation of user-defined conditions. In general, a user specifies a list of conditions and corresponding return values. Case This function evaluates multiple expressions until a condition is determined to be true, then returns a corresponding value. If all conditions are false, a default value is returned.  Case  can be used for categorizing data based on multiple conditions. This is a single-value function. Syntax Case ( Condition1 ,  ReturnValue1 ,  Condition2 , ReturnValue2 ,...,  DefaultValue ) Example Case(([Total Revenue] < 300000), 0, ([Total Revenue] < 600000), 1, 2) sum(Case (Day@DESC in (“Sat”,”Sun”), Sales, 0) {~+} Sum(Case(Category@DESC In("Books","Electronics"),Revenue,0)){~+} CaseV (case vector) CaseV  evaluates a single metric and returns different values according to the results. It can be used to perfo...

Optimizing queries in Microstrategy using VLDB properties

Optimizing queries in  Microstrategy using VLDB properties #vldb #vldbproperties The table b elow summarizes the Query Optimizations VLDB properties. Additional details about each property, including examples where necessary, are provided in the sections following the table. Property Description Possible Values Default Value Additional Final Pass Option Determines whether the Engine calculates...

Microstrategy "Error type: Odbc error. Odbc operation attempted

 "Error type: Odbc error. Odbc operation attempted: SQLExecDirect. [HYT00:0: on SQLHANDLE] [MicroStrategy][ODBC Oracle Wire Protocol driver]Timeout expired" is shown when executing reports from Web When users are trying to execute some reports in MicroStrategy web in particular, they may receive the Error “SQL Generation Complete Index out of range” and “Timeout expired” error as shown below: Possible Causes: One possible cause is that the MicroStrategy Intelligence Server using a cached database connection that was already dropped by the RDBMS. To resolve this: Admin should delete the database connection caches and create a new DSNs in case they are sharing DSNs to connect to different databases. In addition, change the settings for the ‘Connection lifetime’ and the ‘Connection idle time out’.  Follow the steps below to perform the mentioned changes and verify the report after each step and some of the settings require i-server r...

Control the display of null and zero metric values

Show   Control the display of null and zero metric values in a grid report You can determine how to display or hide rows and columns in a grid report that consist only of null or zero metric values. You can have MicroStrategy hide the rows and columns in the following ways: Hide rows and columns that consist only of null metric values Hide rows and columns that consist only of zero metric values Hide rows and columns that consist only of null or zero metric values (default) Once you have defined how MicroStrategy hides null and zero metric values in the grid, you can quickly show or hide the grid using the Hide Nulls/Zeros option in the Data menu, as described below, or by clicking the  Hide Nulls/Zeros  icon  in the Data toolbar. To determine how null and zero metric values are displayed or hidden in a grid report Open the report in Edit mode. From the  Tools  menu, select  Report Options . The Report Options...

Settings for Outer Join between metrics in MicroStrategy

Settings for Outer Join between metrics in MicroStrategy MicroStrategy adopts multi-pass logic to determine the execution plan for a report. This means that every metric is evaluated in separate SQL passes. Outer Joins come into play when MicroStrategy Engine merges the results from all SQL passes into one report. For a multi-pass report, different Outer Join behaviors can give the user completely different results. In addition, report metrics can be of different types which can, in some cases, influence the result of the outer join. In MicroStrategy, there are two settings that users can access to control Outer Join behavior : Formula Join Type and Metric Join Type . Metric Join Type: VLDB Setting at Database Instance Level Report and Template Levels Report Editor > Data > Report Data Options Metric Level   Metric editor > Tools > Metric Join Type Control Join between Metrics Formula Join Type: Only at Compound/Split...

System Manager workflow to execute on a schedule

Creating a System Manager workflow to execute on a schedule System Manager workflow can execute on a schedule or after an event has been triggered. This can be accomplished by creating a simple batch file, and scheduling that batch file to execute with a third-party tool like Microsoft Task Scheduler.   Note : To avoid user permission conflicts, the following steps must be performed with highest privileges.   In the below example, the workflow makes the i-server restarts every day.   1. The user must first have a valid workflow. This particular workflow is a template that is delivered out-of-the-box with System Manager.   2. Save the workflow in  .smw  format.   3. In a text editor (such as Notepad), enter the command line statement that the task scheduler should execute.     MASysMgr.exe -w C:\filename.smw” “UserName=User1 “Password=1234”   4. Save the file in  .bat  ...

Multi-Table Data Import(MTDI) from one or more supported data sources

Multi-Table Data Import(MTDI) from one or more supported data sources In MicroStrategy Analytics Enterprise Web 10 onewards, users can now simultaneously import two or more tables from one or more supported data sources, this feature is called Multi-Table Data Import (MTDI) which has been renamed as Super Cubes in MSTR 2019 (Does it sound like multisourcing for all the users without admin help?) Currently, all connectors in MicroStrategy Web 10 except " OLAP " and " Search Engine Indices " support Multi-Table Data Import. Users are able to add multiple tables/files when doing data import from single connector, as shown below: Users are also able to combine multiple tables/files from different sources and store them into one single Intelligent Cube, as shown below:

mstrio – Python and R wrappers for the MicroStrategy

mstrio – Python and R wrappers for the MicroStrategy REST APIs Connecting to MicroStrategy  Create a connection to the Intelligence Server using   Connection()   and    connect()  in Python and R, respectively. Required arguments for the   Connection()  function are the URL for the MicroStrategy REST API server, MicroStrategy Intelligence Server username and password, as well as the MicroStrategy project name. By default, the   connect()  function anticipates your MicroStrategy Intelligence Server username and password. LDAP authentication is also supported. Use the optional argument    login_mode=16    in the    connect()  function for LDAP authentication.  Extract data from cubes and reports  To extract data from MicroStrategy cubes and reports, use the   get_cube()  and   get_report()  functions. Use...
MicroStrategy Developer Preferences options are expanded so big that some options are being cutoff. Show the hidden objects in the  Microstrategy  developer MicroStrategy Developer Preferences options are expanded so big that some options are being cut off. The steps below given in the MSTR article may not work. This can be simple handled by using the steps below:  In the Microstrategy Developer go to Tools -> Preferences (Not my prefernces :) ) Under Developer category -> select Browsing on the browsing tab you see all the options like below: 3. Now using the mouse place the cursor on text box of 10000 which is next to 'Maximum number of monitoring objects displayed per page. 4. Then Hit Tab on Keyboard and hit another Tab on keyboard 5. Then press the space or down arrow on keyboard and click on OK or Enter. That will show the hidden objects in the Microstrategy developer   Normal Version ...