Optimizing and Maintaining Your Project

Optimizing and Maintaining Your Project

Once your MicroStrategy project is set up and populated with schema objects, you are ready to start thinking about ways to better maintain the project and optimize it for both the short and long term.

This chapter introduces you to maintenance and optimization concepts such as tuning the interaction between your data warehouse and your project, creating aggregate tables, and using partition mapping, and explains how to use these methods to enhance your project. You can find this information in the sections listed below:

Updating your MicroStrategy project schema—As you continue to enhance the design and functionality of your project, you will need to make various schema changes. To see any enhancements and changes to your project schema, you must update your project schema.
Data warehouse and project interaction: Warehouse Catalog—As your data warehouse changes to meet new data logging requirements, your project must reflect these changes. This can include adding new tables to your project or removing tables that are no longer used. You can also tune the interaction between your data warehouse and your MicroStrategy project to bring your data into MicroStrategy in a way that meets your requirements.
Accessing multiple data sources in a project— With the MultiSource Option in Intelligence Server, you can connect a project to multiple relational data sources. This allows you to integrate all your information from various databases and other relational data sources into a single MicroStrategy project for reporting and analysis purpose.
Improving database insert performance: parameterized queries— MicroStrategy’s support for parameterized queries can improve performance in scenarios that require the insert of information into a database.
Using summary tables to store data: Aggregate tables—Aggregate tables store data at higher levels than the data was originally collected in the data warehouse. These summary tables provide quicker access to frequently-used data, reduce input/output and other resource requirements, and minimize the amount of data that must be aggregated and sorted at run time.
Dividing tables to increase performance: Partition mapping—Partition mapping involves the division of large logical tables into smaller physical tables. Partitions improve query performance by minimizing the number of tables and records within a table that must be read to satisfy queries issued against the warehouse.