The Qlik Associative Big Data Index is a powerful value add product for Qlik Sense– delivering Qlik’s patented associative difference engine on top of Big Data – allowing users to freely explore and search big data repositories while leaving the data where it resides.
The Qlik Data Catalyst Prepare module, is where you create custom data preparation jobs called data flows. Data flows transform and augment existing data entities into new sets of data entities, with the specific format and content that you need.
With Qlik Data Catalyst, when you onboard data into the marketplace, you do much more than just ingest that data source into the data collection. Under the covers, Qlik Data Catalyst's onboarding process performs data translation, quality checking, validation, and profiling steps, all aimed at adding an accurate, complete, and thoroughly documented representation of that new data.
With Qlik Data Catalyst you can deliver purpose-built data sets to data consumers across the business - including data scientists, business analysts and downstream applications – which of course includes our powerful Data Analytics Platform Qlik Sense.
Qlik Data Catalyst builds a secure, enterprise-scale catalog of all the data your organization has available for analytics, no matter where it is. Powerful, automated data preparation and metadata tools streamline the transformation of raw data into analytics-ready information assets. Business users get a single, go-to data marketplace to find, understand, and use any enterprise data source to gain insights.
The Data Catalyst Catalog is an interactive Marketplace Dashboard that provides immediate insight and actions on entities across your data ecosystem. Here you can see all the data entities that are part of the Qlik Data Catalyst catalog. Every tile represents a different entity or table of data.
The Associative Difference is a very unique and patented capability of the Qlik Associative Engine. It combines elements of free exploration and discovery along with uncovering findings that would most likely go unnoticed with traditional query-based and SQL tools.