The True OLAP

OLAP or simply OnlineAnalytical Processing is the process that allows users to conduct multidimensional interaction analysis operations on real-time business data. This includes performing operations such as drilling, aggregating, pivoting, and slicing multidimensional data.

It is necessary to create topic specific data cubes in advance to support above operations, thereby users can inspect data in tables or graphs and conduct real time pivoting and drilling. Having said that, let’s consider whether OLAP is enough for catering analysis and forecasting in real world.

Figure 1: Information Systems can be divided into transnational (OLTP) and analytical (OLAP). In general OLTP provide source data to data warehouse, whereas OLAP helps to analyze it.

A mature company may have somewhat large data accumulated about its operations. These data can be used to make certain guesses about the business they are engage in. For example, a vehicle importer may guess what kind of people are tending to buy what kind of vehicles. These guesses are just the basis for forecast. Then the company could utilize accumulated data to evaluate above guesses. When a guess evaluated to be true they can be used in forecast and when it is false they will be re-guessed.

Above process could be referred as evaluation process, whose purpose is to justify conclusions with evidence find in historical data. In business analysis process, a query like the first n customers who has purchased a vehicle from vehicle types contributed for half of the sales volume of the company in the year the x is ubiquitous and required some form of a computation or querying, with intermediate steps.

The requirement of building the data cube in advance, and a limited set of actions available to perform against data cube are limiting the analysis process in a situation like above. The data model needs to have capabilities of reconstructing the cube or temporarily build cubes to cater diverse analysis demands. Furthermore, most of the OLAP products are more famous for their rich user interface; only a few has powerful online analytical capabilities.

Figure 2: In OLAP database there is aggregated, historical data, stored in multi-dimensional schemas (usually star schema).

So what kind of an online analytical tool could fulfill the evaluation process? Theoretically, steps for evaluation can be considered as computation regarding data. This computation can be defined by user and can decide next computation actions to be taken based of the intermediate results without having a defined model beforehand. Additionally this computation should support performing actions on huge amount of data instead of simple numeric computations. At this point of view, SQL is somewhat fulfilling this requirement, but considering its own computational capability, still it has its own limits on solving problems similar to above mentioned problem. This leaves us in a position to think about the limitations of SQL and builds a way through it to make a new generation of computational system for evaluation process, namely, the real OLAP.

I’m still completely a novice in Business Intelligence. J