Skip to main content

Data Mart Reports in Microstrategy

Creating Data Mart Reports in Microstrategy  

When there is requirement to store all the report results to a database table you can use the interesting feature in Microstratgey called Data Mart Reports.

To create a data mart table, you first create a data mart report that defines the columns of the data mart table. You then create the data mart table and populate it with data.
The steps below walk you through the process of creating a data mart report and then executing the report to create a data mart table. The steps also include an example for most steps, based on Tutorial sample data in the MicroStrategy Tutorial project.





              

Follow the simple steps below to create a datamart report:


1 In MicroStrategy Developer, create a new report or select an existing report to use as the data mart table. The report should contain the attributes, metrics, and other objects that you want to use as columns in the data mart table and which will populate the data mart table when the data mart report is executed.
Your report cannot be used as a data mart if it contains any of the following:

View filters

Report Objects that are not included in the template

Derived metrics

For this example, use the sample Tutorial project to create a new report with Customer Region as the attribute and Revenue as the metric.

2 From the File menu, select Save, and select an appropriate folder in which to save the report.

For this example, save the report with the name My_Report, in a folder of your choice.

3 To use the report as a data mart report, from the Data menu, select Configure Data Mart. The Report Data Mart Setup dialog box opens, as shown below:

4 On the General tab, from the Data mart database instance drop-down list, select a database instance for the data mart table that will be created. The data mart table will be stored in this space.

For this example, choose Tutorial Data.

5 In the Table name field, type a table name that you want to associate with the database instance that you specified. This table name must be compliant with the naming conventions supported by your database.
The table name that you enter in this tab is not validated by the system. Ensure that the table name follows the naming convention rules for your database platform. If you do not use a valid table name, an error message is displayed.

For this example, name the table AGG_REG_REV.

6 To use a placeholder in the table name, select the This table name contains placeholders check box.
Placeholders allow you to modify table names dynamically according to your needs. The available placeholders for data mart table names are listed in the following table:
Placeholder
Replacement Options
!u
User name
!d
Date on which the table was created
!o
Report name
!j
Job ID
!r
Report GUID
!t
Timestamp
!p
Project Name
!z
Project GUID
!s
User session GUID
If you use a placeholder character other than those listed in the table, the placeholder is deleted from the table name.
For this example, disable the This table name contains placeholders check box.

7 Select whether to Create a new table or Append to existing table, described below:

Create a new table: Select this option to replace the existing table each time the data mart report is run. The SQL statements drop and create the table each time the report is run.

Append to existing table: Select this option to add the data mart report results to an existing table.

For this example, select Create a new table.

8 If you need to specify governors, table creation settings, and custom SQL for table creation, see Specifying governors, table creation options, and custom SQL statements

9 Click OK.

Create the data mart table


10 Execute the data mart report. MicroStrategy creates the data mart table in the database you selected.
When the data mart table is created, the system displays a message that includes the data mart table name and a notification that the data mart table creation was successful, as shown in the example message below:

Comments

  1. We all know that data warehousing as a service is a kind of outsourcing model in which the service provider manages the software as well as hardware resources.

    ReplyDelete

Post a Comment

Popular posts from this blog

Microstrategy Custom number formatting symbols

Custom number formatting symbols If none of the built-in number formats meet your needs, you can create your own custom format in the Number tab of the Format Cells dialog box. Select  Custom  as the Category and create the format using the number format symbols listed in the table below. Each custom format can have up to four optional sections, one each for: Positive numbers Negative numbers Zeros Text Each section is optional. Separate the sections by semicolons, as shown in the example below: #,###;(#,###);0;"Error: Entry must be numeric" For more examples, see  Custom number formatting examples . To jump to a section of the formatting symbol table, click one of the following: Numeric symbols Character/text symbols Date and time symbols Text color symbols Currency symbols Conditional symbols Numeric symbols For details on how numeric symbols apply to the Big Decimal data type, refer to the  Project Design Guide . ...

Reduce Intelligent Cube Size By Finding Intelligent Cube Objects Which Are Not In Use

Reduce Intelligent Cube Size By Finding Intelligent Cube Objects Which Are Not In Use If the i-cubes can potentially be reduced in size an audit can be performed on the cube objects to see which cube objects are not being used by any of the view reports, documents, or dossiers.   The below are examples for a few of the common metadata database platforms . NOTE: To perform this audit, queries are run against the MicroStrategy metadata database. Ensure a metadata backup is taken prior to performing the below actions. Steps: 1) Identify the object ID of the Intelligent cube to be audited by checking the objects Property window 2) Identify the object ID of the project this cube exists within by opening the Project Configuration Sample Cube ID =   CFAF1E9B4D53990698C42E87C7AF2EB5 Sample Project ID =  B7CA92F04B9FAE8D941C3E9B7E0CD754   3) Run the below SQL against the metadata database by replacing the Cube ID and Project ID within the respective ...

Compound key attribute

Compound key attribute A compound key attribute is an attribute whose primary key is made up by the combination of two or more columns. The multiple columns are joined with other attributes, typically in a many-to-many relationship . To create a compound key, users must create multiple attribute forms, group them together and set the form group as the key for the attribute. Use the same steps as specified in the help menu: Open attribute editor (right-click on attribute and select 'Edit') Select the forms that will make up the compound key From the 'Edit' menu, choose 'Group' NOTE: Modifying the key form will trigger required updates when saving. This may make related application objects (reports, filters and metrics) unusable. Click on 'Yes' to continue, when prompted, in a dialog box, to confirm this action Save the changes. Choose 'Update Schema' from the Schema menu

Algorithm to calculate Logical Table Size in Microstrategy

How are the fact tables determined using the logical table size for SQL generation 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.   IMPORTANT:   The system hierarchy is defined by the parent-child relationships between attributes of the same family (formerly known as a dimension), not by user-defined hierarchies (i.e., drilling hierarchies).   MicroStrategy Engine utilizes an algorithm based on attribute keys to calculate the Logical Table Size (LTS): Given the following tables: ...

Microstrategy Removing sections that do not have metric data

Removing sections that do not have metric data This is an interesting feature which might not be explored by many of us and it comes us handy. A  cross join between datasets can result in rows or Group Header/Footer sections that do not have metric data. For example, a document contains two datasets. Dataset 1 contains Year and Revenue, with data for three years (2007-2009). Dataset 2 contains Year and Profit, filtered to return data for only two years (2008 and 2009). If you place Year and Profit in the Details and execute the document, it displays three rows, although no profit data exists for 2007. This is a product of the cross join between the two datasets. You do not want to see the blank line for 2007 since it does not give you any data for profit. You can select the  Trim sections for which no metric value data is available  check box. This removes the row for 2007, since no metric data for Profit is available for 2007. The results are shown below: ...

Create a transaction services photo uploader

Create a transaction services photo uploader   1.  Create a new table "photo_upload" in Tutorial warehouse database (the default location: C:\Program Files\MicroStrategy\Tutorial Reporting\TUTORIAL_DATA_7200.mdb), as shown below:    2. The 'photo_upload' table has to be pre-populated with *exactly* 10 rows of data, the values for the 'ID' column should be 1-10 and the values for the 'uploaded' column should all be 0 3.  In MicroStrategy Desktop, create a freeform report "R1" based on the new table "photo_upload" in Tutorial data created at step 1, as shown below:   SELECT Location, Description, ID, uploaded, numbers FROM PHOTO_UPLOAD 4.  Create another table for transaction insert SQL. Make sure to create an 'autonumber' type ID as primary key for this table, or auto_increment ID for different DBs.                     5. Create...

Predictive modelling in Data Science using Microstrategy

Creating a predictive modelling in MicroStrategy MicroStrategy Data Mining Services has been evolving to include more data mining algorithms and functionality. One key feature is MicroStrategy Developer’s Training Metric Wizard. The Training Metric Wizard can be used to create several different types of predictive models including linear and exponential regression, logistic regression, decision tree, cluster, time series, and association rules. Linear and exponential regression The linear regression data mining technique should be familiar to you if you have ever tried to extrapolate or interpolate data, tried to find the line that best fits a series of data points, or used Microsoft Excel’s LINEST or LOGEST functions. Regression analyzes the relationship between several predictive inputs, or independent variables, and a dependent variable that is to be predicted. Regression finds the line that best fits the data, with a minimum of error. For example, you have a dataset ...

Scheduling a report or document to be sent to an FTP in MSTR

Scheduling a report or document to be sent to an FTP server You can have a report or document automatically delivered to a location on your FTP server on a specific schedule. To do so, you must subscribe to the report or document, as described in the steps below. You can customize your subscription by typing macros in the  File Name ,  Sub-folder , or  Zip File Name  fields. These macros are automatically replaced with the appropriate text when the report or document is delivered. For example, you create a subscription to a document. If you type  {&Project}  in the  File Name field, the name of the project in which the document is saved is displayed in the name of the document when it is delivered. • This procedure assumes that an administrator has already added your FTP server as a new device in Developer. Steps to do so are included in the  System Administrator Help . To send a report or document to an FTP server on a schedule ...

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...