Big Data is comprised of structured and unstructured data being generated by social networks and the internet of things (IoT), personal electronics and apps, marketing questionnaires, product purchases, and so much more. The expansion of IoT, connected devices and people is generating volumes of data that is exceeding the storage capacity of traditional database systems. By some estimates, we generate as much as 2.5 quintillion bytes of data each day.
With Big Data comes big challenges, including:
– The inability to quickly and easily access all types of data, locked within storage silos, in order to perform business analysis and reporting.
– Time, cost and resource consuming extract, transform, load (ETL) processes which also inhibits near real-time analysis.
– IoT data sets are unstructured and without business context, often in formats that are not suitable for storing in relational database tables or for querying using relational query semantics.
You require a solution that bridges business/operational data stored in relational databases with IoT data to generate true, real-time, Business Intelligence (BI) that leads to self-learning intelligent applications and business processes.