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2 min read - 4 min video
In this week's Qlik Design Blog I have the pleasure of introducing our newest guest blogger, Michael Distler. Michael is a Director of Product Marketing responsible for developing content, positioning, and messaging for Qlik products. His major focus is on data related topics such as Qlik Connectors and Big Data. Today Michael presents a number of approaches that Qlik offers when it comes to handling Big Data.
Qlik's Approaches with Big Data
Just like the term Big Data doesn’t equate to one technology, Big Data also doesn’t relate to one scenario, use case or infrastructure. There can be many differences from one organization to the next. Since every situation is different, Qlik offers multiple techniques which can be used individually or in combination to best meet the Big Data needs of a particular customer.
These approaches include but are not limited to:
- Our default in-memory architecture (QIX)
- Segmentation
- Chaining
- A Hybrid in-memory / direct access approach using Direct Discovery
- On Demand App Generation
Rather than write about these, I created a brief (4 min) video presentation that reviews the different Qlik methods that can be utilized with Big Data including a brief demo of Qlik’s newest technique On demand app generation (ODAG).
To learn more about these approaches and how Qlik works with Big Data you can also download this whitepaper.
Regards,
Michael Distler (@michaeldistler) | Twitter
Director, Product Marketing
Qlik