InetSoft Tools & Technology: What is Online Analytical Processing (OLAP)?

Below is a continuation of the transcript of the April 2016 Webinar hosted by InetSoft on the topic of OLAP, the basics of what it is and an explanation of some of the technology terms related to, what OLAP's benefits are, and what the choices in OLAP technologies and OLAP tools are. The speaker is Mark Flaherty, CMO at InetSoft.

Mark Flaherty (MF): In terms of a higher level definition of analytical techniques related to processing, there is a common tool or technique called OLAP. OLAP is the acronym for "Online Analytical Processing." The literal meaning of this words is misleading and dates back decades ago to early computing. Nowadays OLAP means being able to cut your data up and aggregate it up into an environment that allows you to do multi-dimensionality analysis.

So this means the ability to look at trends, do time-based analysis along a variety of dimensions. This gives you drill-through or down capabilities. You can expand your data hierarchy so you can look at all different levels of your data. The cube model in the industry has been used for many years and is supported by many vendors. MDX is commonly used to express and query against your OLAP environment. In 2001, there was a standard created for XML for analysis, called XML/A, a new format or a method which you could call MDX using an XML interface.

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So there are a variety of techniques or approaches to OLAP. We’ll talk about what InetSoft specifically supports in a few minutes. But there are different techniques of multi-dimensional OLAP, which is often called MOLAP for short. This is something that is usually a proprietary cube-based environment. There is also ROLAP, or relational OLAP, which is taking advantage of a relational hierarchy in an RDB, or relational database, to structure your data to do your summarizations and aggregations.

Then there is a combination of both called hybrid OLAP which takes advantages of some of the multidimensional aspects of OLAP, its proprietary-based format, combined with the open-standards ROLAP. This is meant to set a high-level context for OLAP, where it sits, and why it is useful and commonly taken advantage of for analysis.

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