Data Intelligence, Business Analytics
Many BI practitioners have heard about OLAP which is an important constituent part of business intelligence. And today we will talk about what OLAP is indeed for actual need? What is real OLAP? What is instant OLAP for instant data analytics?
Understood literally, OLAP is online analytical processing, that is, users conduct analytical operation on real-time business data.
But, currently the concept of OLAP is seriously narrowed, and it only refers to operations such as conducting drilling, aggregating, pivoting and slicing based on multi-dimensional data, namely, multi-dimensional interaction analysis.
To apply this kind of OLAP, it is necessary to create in advance a group of topic specific data CUBEs for data analytics in OLAP tool. Then users can display these data in the form of crosstab or graph and conduct in various real-time transformations (pivoting and drilling) on them, with the hope to find in the transformation process a certain law of the data or the argument to support a certain conclusion, thereby achieving the aim of data analytics.
Do we need this kind of OLAP?
To answer this question, we need to carefully investigate the real application process of the OLAP, thereby finding out what the technical problem the OLAP tools needs to solve is on earth.
Employees with years’ working experiences in any industry generally have some educated guesses about the businesses they engage in, such as:
A stock analyst may guess stocks meeting a certain condition are likely to go up.
An employee of an airline company may guess what kinds of people are accustomed to buying what kind of flights.
A supermarket operator may also guess the commodity at what price is more suitable for the people around the supermarket.
Evidently, this type of computation demand is ubiquitous in business analysis process and all can be computed out from historical database. Then how about instant data analytics, not from historical database?
To be continued...