Learning Data Warehousing and OLAP -part I
Today I am going to talk a little about my own learning experience as a Microsoft Technical Writer writing for the PerformancePoint Server team.
I remember going around and asking for advice on what to learn quickly when I began writing for the PerformancePoint team. The advice that I received from a senior program manager at Microsoft is something I would like to share with you. Get ready, it is simple. Learn OLAP!
So in my journey to learn online analytical processing (OLAP), I began searching the Web for answers, read a lot of books, looked at a lot of star schemas and schemas in SQL Server 2005, built some cubes, integrated some data, and read Ralph Kimball books. The following are a few simplified bits that helped me conceptualize OLAP.
- A data warehouse is a repository for storing and analyzing numerical information. Core data in the data warehouse are typically numeric values that can be summarized (or aggregated). A great place to visit for learning this is the Data Warehousing Information Center.
- One reason for a different kind of database is that pulling data can prove to be very, very expensive in resources. Data warehouses allow you to store aggregated data -rather than ad-hoc summing a resource-expensive query.
- An OLAP cube is a borrowed term to describe the integration of the fact table with dimension tables.
- OLAP cubes contain lots of metadata; metadata in its simplest definition is data about data.
- Multidimensional expressions or MDX is a metadata-based query language that helps you query OLAP cubes.
I’ll post a few more in another blog entry (Learning Data warehousing and OLAP part II) and explain how it ties to PerformancePoint Server products.
What does it have to do with Business Intelligence?
Business Intelligence (BI) makes use of a data warehouse and takes advantage of OLAP tools. The following is an oversimplified diagram that may bring BI, OLAP, and data warehousing together for you.
An example of a report that is fed by fact data.
I created this small diagram for my own sanity while studying OLAP. It gives me a simplified visual of how dimensional data might look in a report or in a query result. After you read information on data warehouses, star schemas, dimensions, fact tables, etc... this diagram might bring some of it together for you.
