Data processing is to critical to supporting organizations’ everyday operations such as generating reports for suppliers and customers, measuring internal metrics day to day, and reporting quarterly financial results. Effective data processing operations enable companies to efficiently create products that revolutionize how people communicate, shop, manage their finances, and learn about the world.

Leading organizations have mastered the art of collecting data and bringing it into a system that can store and make data accessible to the enterprise for increased operational efficiency.
For example, telecommunications firms collect detailed records about how each call is initiated and routed in order to provide accurate bills and to ensure high service quality. Online retailers track what consumers browse and buy to make smart inventory decisions and to guarantee high quality and timely shipments. Financial firms combine market data with individuals’ transaction details so they can be certain that money is being managed and transferred correctly.

Raw data is generated from sources like call detail records (CDR), point of sale (POS) transactions, web browsing and clicks, electronic medical records (EMR), financial trades, and data management tools such as enterprise resource planning (ERP) systems. In traditional IT infrastructures, an extract, transform, load (ETL) process is employed to collect raw data from various sources, transform it into a consistent format that can be understood by relational database management systems (RDBMS), and then load it into the database or data warehouse for storage and analysis.