Partitioning data into datasets
This use case describes the various high-level steps required to work with datasets. You can use datasets to partition configuration data into subsets, each representing a logical group of configuration items (CIs) and relationships. The same real-world object or relationship can be represented by instances in more than one dataset. For example, different discovery applications can create CI and relationship instances in different datasets. You can later merge those instances into a single production dataset.
Scenario
Scenario
Calbro Services needs to discover various hardware and software, bring relevant information from the payroll services, compare this data and put preferred pieces of information in the production dataset.
Calbro Services uses the BMC BladeLogic Client Automation product to discover the desktop and laptop computer systems, (including hardware and software) used by Calbro Services employees. This information is stored in the BMC Configuration Import dataset of BMC CMDB.
Calbro Services also uses BMC Discovery to discover information about the servers, software, and other devices used to deliver banking information to Calbro Services customers. This data is stored in the BMC.ADDM dataset.
Lastly, Calbro Services uses a third-party discovery tool to collect information about the equipment that supports the corporate payroll services. Calbro Services uses Atrium Integrator to bring relevant data from the payroll database into BMC CMDB. The administrator creates a new dataset named Calbro Payroll specifically for this information.
Because some of the instances in these different datasets might represent the same real-world CIs, the administrator configures BMC CMDB reconciliation jobs to compare those datasets against each other and put the preferred pieces of information in the production BMC Asset dataset.
Workflow
Working with datasets involves these high-level steps:
- Identify your data sources.
- Create a dataset for each data source that you have identified.
- Import your data source content into the relevant dataset.
Results
After performing these tasks, you can partition data according to the providers of that data. Each discovery application that you use can store the data that it discovers in a separate dataset.
Benefits
You can define processes and operations for a dataset depending on the the nature of source which provides that data.
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