Managing data marts for custom views

A data mart is used to prepare data for a custom view. 

BMC Helix Continuous Optimization provides the following types of data marts:

To access the Data marts page, click Administration > Data marts

The Data mart page lists the Out-of-the box and custom data marts available in the system. You can filter the data marts according to the type of data mart. In addition, you can add or edit custom data marts, or materialize data marts from this page. The data marts created using the Summary Data Mart wizard are also displayed on this page. 

The following information is displayed in the Data marts page:

FieldDescription
IdID of the data mart.
Name

Click the name of a data mart. The details page shows the SQL code of the SQL data mart. 

You can edit or delete the data mart from the details page.

Identifier

Unique identifier associated with the data mart. This identifier can be used in the SQL query while creating dependent data marts.  

DescriptionDescription of the data mart.
TypeType of the data mart.
Status

Status of the data mart. The status could be OK, Error (the data mart has some issues), or Warning (the dependent data mart is in Error).

Click the name of a data mart that shows the status as Error or Warning to view the probable cause and suggested actions. For more information, see Troubleshooting data marts.

Creation DateCreation date of the data mart.
PackageIndicates whether the data mart is out-of-the-box or custom.

Overview of SQL-based data marts 

A SQL-based data mart is a standard SQL data mart statement managed by BMC Helix Continuous Optimization in terms of creation and materialization. You can use the SQL-based data mart to manipulate data retrieved from the database tables that are created by one or more summary data marts. For example, you have a custom view that displays the CPU and memory utilization of virtual machines and you want to view the top 5 virtual machines according to their CPU usage. You can use the SQL-based data mart to retrieve this information. 

If a summary data mart is not created, the database is empty. Therefore, make sure that you create at least one summary data mart before creating SQL-based data marts.

Using a SQL-based data mart, you can complete the following tasks:

  • Rename the columns by using more appropriate labels
  • Select only the data series, metrics, and statistics of interest
  • Group results

A SQL-based data mart can be populated:

  • On-the-fly when the query is performed, which is the standard behavior.
  • By a SQL-based data mart Materializer Task that creates a table and populates it with the content of the SQL data mart (called Materialized SQL data mart). The Materializer task runs according to a specific schedule.

For details about creating a SQL data mart, see Creating a SQL-based data mart for a custom view.

Overview of summary data marts 

A summary data mart is used to collect the time series data from the metrics store for a specified period. Hourly data points are extracted for the specified period and aggregated to a single point. While aggregating data, you can specify the type of statistics that you want to collect. For example, average value, minimum value, maximum value, summation, or percentile value. To retrieve this statistics, you can configure the following properties while creating a summary data mart: statistics and statistic

For more information about configuring these properties, see Using the advanced editor of the summary data mart wizard.

Overview of analyses, models, and reports data marts 

The analyses, models, and reports data marts contain data that is generated by the analyses, models, and reports. You can use these data marts for administering specific scenarios. For example, you can use them to check the number of analyses, models, and reports created by each user. 

These data marts are available for use after you install the Works Administration Data Marts package on the Maintenance page. For information about installing packages, see Performing system maintenance tasks. After you install the package, the materializer task for these data marts is automatically created and started, and the following data marts are listed on the Data marts page:

Works Admin - Analyses

Provides the following information about each analysis that is active in your environment:

  • The name and description
  • The template and domain
  • The date and time stamp when the analysis was created and run
  • The user who created the analysis
  • The access mode that indicates whether the analysis is available to all users

Works Admin - Models

Provides the following information about each model that is available in your environment:

  • The name, description, type, and ID
  • The scenario name, description, and ID
  • The date and time stamp when the model was created
  • The user who created the model
  • The access mode that indicates whether the model is available to all users

Works Admin - Reports

Provides the following information about each report that is created in your environment:

  • The report name, description, and type
  • The template and domain
  • The date and time stamp when the report was created and last run
  • The export formats
  • The user who created the report
  • The reporter task
  • The access mode that indicates whether the report is available to all users
  • The mail recipients with whom the report is shared
  • A list of CC and BCC mail recipients with whom the report is shared

You cannot edit, delete, or export these out-of-the-box data marts. You can create custom SQL data marts based on these data marts to fetch specific data according to your requirement. 

Overview of Gateway Server Status data mart

The Gateway Server Status data mart displays the status data of the Continuous Optimization agents. This data mart is automatically materialized and is available in the Administration > Data Marts section. It contains information about the status of data that is collected from the gateway server agent machines and then stores the last 30 days of status data. You can use this data while creating a custom view or combine this data with other data marts, like, SQL-based data mart or the Summary data mart. Information such as, system ID, task ID of the ETL, system type ID, system type name, etc. is displayed. For details, see Using the Gateway Server Status data mart.

To edit or delete a custom data mart

You can edit or delete a custom data mart only if your user role is assigned the permission to modify a data mart. For more details, see Configuring authorization profiles.

You cannot modify or delete an out-of-the-box data mart. 

  1. In the Data marts page, select a data mart.
  2. Click Edit or Delete to edit or delete the required data mart.
  3. Steps for editing a data mart are same as the steps for adding a data mart. For more details about editing data marts, see Creating a SQL-based data mart for a custom view.

To materialize a SQL-based data mart

You can materialize a data mart only if your user role is assigned the activity to materialize a data mart. For more details, see Configuring authorization profiles. The frequency of materialization of the data mart depends on the associated task. For more details, see Configuring the Data Mart Materializer task

  1. Select Administration > Data marts.
  2. Select a data mart and click Materialize now.

To export and import custom data marts

You can export and import custom data marts and reuse them in multiple environments of BMC Helix Continuous Optimization, without having to recreate them. For example, if you have created a custom data mart in the development or test environment and after confirming that the results are accurate, you can export this data mart as a data mart package file. This package file can then be imported in the production environment. 

If the selected data mart is using any data marts or being used in other data marts, all these data marts, that is, the entire hierarchy tree gets exported and hence can be imported in the destination environment. 

You can not export or import out-of-the-box data marts. 

To export a data mart

  1. Select Administration > Data marts
  2. Select a custom data mart, and click Export. Select the location to save the exported data mart. 
    The data mart is exported as the data mart package file with the file extension .dpkg. 

To import a data mart

  1. Select Administration > Data marts
  2. Click Import data mart package
  3. Click Browse to select the data mart package file (.dpkg) that you want to import. 
  4. Click Upload

If your destination environment includes any data marts with the same identifier as one of the data marts being imported, the existing data marts are updated by the imported data marts. A message is displayed indicating the same. You can choose to Proceed or Cancel the import. 
All imported data marts are listed in the Data marts table. 

Example that shows the export/import flow

Consider that you have exported the VMware systems data mart with identifier as ER_V_VMWARE_SYS. This data mart has a related data mart as VMware hosts.

The destination environment contains the VMware VMs data mart with the identifier as ER_V_VMWARE_SYS.

After you import, the the VMware systems data mart overwrites the VMware VMs data mart as both have same identifiers. The related data mart, VMware hosts is linked to the VMware systems data mart.

In the following diagram, red text indicates data mart names and blue text indicates identifiers. 


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