High performance data discovery

Business Intelligence has always been one of the sectors of excellence of PRAXI’s IT Division, which boasts a successful history of over thirty years in the development and implementation of solutions in this area, using different technologies carefully chosen among the "best-of-breed" proposals of the period based on design and planning needs, with the constant goal of being able to propose the best application solutions.

From the beginning of 2010, while maintaining its collaborations in previously covered technological areas, after a series of analyses on the technological, qualitative and innovative requisites relative to the proposals of the major vendors, PRAXI decided to undertake a strategic partnership with QlikTech Italia, having recognised the optimum technology in the Qlik platform for the fulfilment of cutting-edge solutions free from design and planning constraints from an application and performance point of view.

As regards its partnership with Qlik, operating in different markets, among which GDO and publishing stand out, PRAXI obtained the Qlik prize "Implementation Partner of the Year", in 2015:

PRAXI’s strategic choice of the Qlik technology was based on three fundamental areas of excellence:

• Associative analyses of the data (data discovery)
• High performance of browsing (in-memory database)
• Rich and flexible analysis and performance tools

Here, we analyse in more detail these three distinctive factors of the Qlik platform that, for several years now, have determined their positioning as leader in the Gartner Magic Quadrant for the Business Intelligence.

The associative method of the data analysis described is based on the in-memory engine of the Qlik technology that, through a “compression” process of the data, makes it possible to transport the whole analytical database into the RAM memory of the machine that hosts the application, eliminating the need for time-consuming periodic re-readings of the data subsets resident in remote Databases.

The presence in the memory of all the data to be analysed guarantees surprisingly brilliant performance in querying and browsing, also in case of large amounts of data (when dealing with traditional large databases or Big Data).

The high speed in the analyses and browsing of the data makes users’ experience extremely fluid and easy, eliminating the waiting phase that irritates users and distracts them from the analyses, sometimes causing them to abandon the solution. This setting also eliminates the need of continuous maintenance of the remote databases aimed at trying to maintain performance of adequate answers to the frequent queries.