We hear a lot about OLAP being an ageing technology replaced by brand new ones, but do we know what OLAP means?
OLAP (Online Analytical Processing) is certainly NOT a technology but a concept that was introduced into the Business Intelligence space over 20 years ago. At that time, business analysts where already struggling to get powerful and flexible insights through ad-hoc SQL queries. OLAP brought the groundbreaking change of decoupling the business model from the physical model and allowing for natural navigation paths, flexible multidimensional calculations, and conceptual data navigation that is intuitive and logical. It introduced a spectacular way for business-analyst-type users to easily perform analyses of large volumes of business data.
The unlimited power of OLAP Cubes
icCube is building on the state-of-the-art principles of in-memory columnar data stores as well as PhD-level mathematics based indexing. Leveraging this technology, icCube lifts all of the constraints that made OLAP cubes look IT intensive and rigid, while at the same time maintaining the compatibility with industry standards in the reporting and analytics world.
Here are a few of the constraints icCube lifted:
- No more need to restructure data into a star or snowflake schema, which is complicated to perform at source level
- Unlimited amount of dimensions and measures
- Moving out of trivial key-like associations (e.g., many-to-many, ranged)
- Drill-through to access the granular underlying raw data
- Categories allowing introduction of new dimensions on the fly to simplify the modelling process
- MDX+ language (functional support, object-oriented extensions, and many new helper functions)
Why MDX/XMLA?
Over time, MDX became a de-facto standard of the OLAP ecosystem even though not as widely used as SQL in relational databases. It standardises the way to analyse and query the data of the OLAP cube and opens the data to almost every reporting tool including Excel through the XMLA protocol surrounding it.
Using MDX once means you will be able to work with almost any other technology vendor in the OLAP space. This is a huge positive differentiator with respect to proprietary querying languages used by the new generation of closed technology vendors. Sometimes it is surprising to see, even though understandable from a revenue perspective, how we move back from an open standard trend to a closed/proprietary one.
icCube and OLAP Cubes
Similar to the original OLAP solutions, icCube and its web reporting are designed to enable solutions where multiple business users perform ad-hoc data analysis on a centralised data repository. On the other hand, icCube does not achieve this by pre-calculating query results, pre-aggregation, or by imposing limitations on the end user, but by utilising state-of-the-art technology.
Powered by its core technology, icCube delivers distinct advantages over legacy OLAP-based solutions:
- Sub-second query times in high dimensionality sparse real-time cubes
- A state-of-the-art IDE allowing for a straightforward modelling exercise
- Possibility to integrate multiple datasources without an intermediate data mart of integration layer
- No limits of number of cubes or dimensionality
- Granular data available all along the analysis flow
- Dynamic expansion of the foundation data model through dynamic categories and calculated members
- Scalability on the hardware you need, from traditional PC running Linux or Windows, or even your entry-level Mac for a small problem, up to very large multi-core high memory for the most challenging business needs