QlikView and Big Data

Using the Power of Big Data analysis for business users

 

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QlikView – Big Data is for everyone

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Detecting new trends in the market early and discovering fraude are the traditional examples for the added value of Big Data. But now that the making of reports and analysis are no longer the exclusive domain of data specialists and the reduced time for analysis, makes Big Data also accessible for the Business User. It is possible, for example, that a general manager is interested in overview data about all the company’s production lines, while a product or regional manager needs more details, but only for the regions under his or her management. In certain cases, for example, a support manager who has to investigate the telephone contacts of one specific customer, it may be necessary to see the unprocessed data.

 

bigdata-visualQlikView’s In-Memory Architecture: Essential for the analysis of Big Data

With the patented data engine in the QlikView memory, data are compressed with a factor 10, which means that a single server with 256 GB RAM, can store up to 2 TB of uncompressed data. This equals billions of data rows while response times only possible with in-memory architectures, are offered.

Other QlikView functions like document chaining and binary load accelerate the process of exploring very large data sets. This is the path taken by many QlikView customers when analysing terabytes of data stored in data warehouses or Hadoop clusters and similar archiving systems.

 

 

Big DataDid your company already invest in Big Data infrastructure? Then check out QlikView Direct Discovery

For companies that have already invested in a large data warehouse or other Big Data infrastructure and don’t want to load all data into the QlikView’s in-memory engine, QlikView Direct Discovery is a hybrid approach that leverages both in-memory data and data that is dynamically queried from an external source.

QlikView Direct Discovery offers 3 big things:

  1. Query data directly from the Big Data repositories
  2. Cache Query-results in memory for faster recall
  3. Maintain associations among all data, wherever it’s stored

This hybrid approach offers business users the possibility to benefit from Big Data with no programming skills and the ability to add context and insight while drilling-down to granular details. 

 

 

Big Data under control with QlikView

Consolidate relevant data from several sources, including Big Data archives
Select the method which is most relevant for you and your IT infrastructure
Make optimal use of existing investments in Big Data infrastructure or data warehouses
Gain access to Big Data’s complex data modelling or programming
Investigate associations between Big Data and traditional data
Visualise Big Data with exiting, advanced graphics
Gain access to and analyse Big Date on mobile devices