OLAP (online analytical processing) is a multidimensional, multiuser, client-server computing environment. It is intended for users who analyze consolidated enterprise data in real time. OLAP systems feature drill-down, data pivoting, complex calculations, trend analysis, and modeling.
OLAP is designed for business managers who need to address complex “what if” questions by creating scenarios to test planning strategies. Users can analyze relationships between data categories such as:
How did Product A sell last month? How does this compare to the same month over the last five years?
Did commissions and pricing affect how salespeople sold Product A?
How will Product B sell next month?
Did Product B sell better in particular regions?
Did customers return Product C last year? Were returns due to defects? Did a specific plant manufacture defective products?
You can use Essbase Studio to build a multidimensional Essbase database to answer these types of questions quickly.
A multidimensional database (MDDB) stores consolidated data at the intersections of its members and dimensions. For example, if a company sells 20 units of products in the East region in the first quarter, Essbase stores 20 at the intersection of Product, East, Quarter1, and Unit Sales.
In a multidimensional database, a dimension is a data category representing a core component of a business plan, and it often relates to a business function. Product, Region, and Year are typical dimensions. In most databases, dimensions rarely change over the life of the application.
In a multidimensional database, a member is an individual component of a dimension. For example, Product A and Product B are members of the Product dimension. Each member has a unique name. A dimension can contain many members. In some dimensions, members change frequently over the life of the application.
Members can be parents of some members and children of others. The Essbase outline indents members below one another to indicate a consolidation relationship.