Data Warehousing Modernization
The traditional data warehouse was built on a well-structured, sanitized, and trusted repository strategy. Today, more than 85 percent of data volume comes from various new data types proliferating from mobile and social channels, scanners, sensors, RFID tags, devices, feeds, and other sources outside the business. These data types do not easily fit the business schema model and may not be cost-effective to ETL into the relational data warehouse.
IT organizations’ challenge is their traditional enterprise data warehouse was never designed to incorporate this explosion of new types of data at this volume and velocity. To drive the business forward, the modern enterprise needs to evolve its enterprise data warehouse to take advantage of big data and do so in real-time. Once all data has been incorporated, business analysts and data scientists uncover new insights that impact the business. To do this, the traditional data warehouse needs to evolve into a modern data warehouse.