UPDATE: Attached are several demos, PDFs and a PPT that are useful to be shared externally for customers and partners alike.
By now it is common knowledge in the Business Intelligence and Data Visualization space, that the term Big Data doesn’t equate to one technology. That being said, it is also true that Big Data 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 organization. One of these approaches is On Demand App Generation, commonly referred to as ODAG. ODAG was first introduced as an extension for previous releases, and is now built in to Qlik Sense starting with our June 2017 release. It benefits from continued enhancements with each release.
Our latest video from Adam will show and tell you more.
"On Demand App Generation is a methodology that can be used in any situation where each user wants to explore their own slice of the data and it is now a built in function since the June2017 release of Qlik Sense. Big data analytics can now be approached through a shopping cart like process where dimensional data can be filtered at an aggregated high level and data slices automatically generated on-demand for further detailed analytics by users, all in a secure and governed manner." - Adam Mayer
Adam joined Qlik in 2016 as a Senior Manager in Technical Product Marketing. He is responsible for delivering the company’s Internet of Things (IoT) go-to-market strategy. With a strong technical background in computing spanning over 20 years, underpinned by an incisive engineering perspective, Adam is an avid follower of new technology and holds a deep fascination of all things IoT, particularly on the data analytics side and finding new ways to make it as translatable, visual and understandable to as many people as possible.
"My first Qlik Sense app tracked my spend on car fuel where I geeked out on the rise and fall of pricing data!"