The Role of Traditional Operational Data in the Big Data Environment
Knowing what data is stored and where it is stored are critical building blocks in your big data implementation. It’s unlikely that you’ll use RDBMSs for the core of the implementation, but it’s very likely that you’ll need to rely on the data stored in RDBMSs to create the highest level of value to the business with big data.
Most large and small companies probably store most of their important operational information in relational database management systems (RDBMSs), which are built on one or more relations and represented by tables. These tables are defined by the way the data is stored.The data is stored in database objects called tables — organized in rows and columns. RDBMSs follow a consistent approach in the way that data is stored and retrieved.
To get the most business value from your real-time analysis of unstructured data, you need to understand that data in context with your historical data on customers, products, transactions, and operations. In other words, you will need to integrate your unstructured data with your traditional operational data.