What is Big Data vs. Business Intelligence?
As element61, we see a Big Data Platform as a complementary set-up to a traditional BI stack. A Big Data Platform supports organizations to handle bigger data volumes and simplify the delivery of intense or real-time analyses while avoiding skyrocketing storage and maintenance costs in their traditional platform. Specific use-cases where Big Data architectures win and traditional BI Data Warehouses fail are digital data, IoT data and AI use-cases.
Figure: Big Data stored in your Big Data Architecture still requires BI tools for discovery and reporting
For years, organizations considered Big Data an IT solution rather than a business opportunity. That changed when disruptors such as Zalando, bol.com, Coolblue, Facebook, Amazon or Google leveraged Big Data to their distinctive advantage: they had a unique 360° view on their customers, a personalized approach to all users, an understanding of social media, etc. Although their success can't be attributed solely to Big Data, their success was fueled by the ability to read, understand and use massive data-sources to take real-time decisions; after all: "what gets measured gets managed".
Today, the essence of Big Data is to keep and use all of your organization's data indefinitely, no matter the size or source. Its added value is bringing together all of the data such that we can answer any type of question and empower the organization to make informed decisions.
Although this market is changing continuously for sure as an Open Source community (Apache), the past years have seen breakthroughs as the world's most mature software providers such as Google, IBM, SAP and Microsoft are now offering a toolbox of solutions designed to abstract the most complex part of the technology and to guarantee integration with known BI solutions. Although all named differently, the most needed Big Data modules return in all service offerings (Microsoft Azure, IBM , Google Cloud Platform). Solutions are offered with a choice of full-cloud, semi-cloud or on-premise.