In my previous entry, I mentioned how our customers are democratizing innovation in data warehousing and data integration. One thing is clear: there is renewed energy around using data to become competitive in the global market. We also have many options in data warehousing –a centralized enterprise data warehouse (EDW), departmental data warehouses and data marts, including appliance options and cloud computing for data warehousing. And yes, we do have an ongoing argument of EDW versus data marts. What’s different at this time is that, it’s the business that’s fueling this debate. A customer may outlaw a data mart because the maintenance costs and risks managing marts outweigh the potential benefits and thus do not meet the operating requirements. Another may opt for a cyclical data mart to allow for faster time to market and analytic flexibility for departmental business needs with a shorter turnaround.
One of our customers in the entertainment industry recently went live with their real-time data warehousing and master data management project. The company decided to compete on customer interaction. So it merged data across 17 properties including 16 years of gaming data and constructed an EDW. They now deploy the data profiling and quality management solutions as part of their enterprise data integration foundation. This enabled them to ensure that they REALLY know the customer preferences and behaviors and treat them with differentiated offerings at multiple touch points in real-time. They are also arming their service staff with historical customer usage and offering extra – rewarding experiences for each guest, using real-time information from their customer data hub integrated with an EDW.
Another Informatica customer, in telecommunication, has multiple large data warehouses and data marts. There are significant data movements across a variety of data repositories. What unifies them is data integration. For example, to enable the mobile workforce in real-time, the firm provides new product or service requests, say modem installation or cable set-up, directly to the workers who are located the closest and available to the specific tasks. This is only possible because the service call triggers each request with the change data capture approach and the data is trustworthy, enough to take actions on. Instead of taking three to four days to upgrade the service, they can do this within a day or even faster. Imagine if you were the customer who needs a connectivity upgrade for an important Web-based session tomorrow, which vendor would you sign up for?
Regardless of the style of data warehousing, organizations are becoming savvy about the timeliness and quality of data they use to distinguish themselves in the market. That’s the reason why more organizations like those mentioned above are adopting data quality and real-time data integration as part of data warehousing. When I listen to their use cases and justifications for having data quality and real-time data integration in data warehousing, they are not just for IT optimization and cost reduction. They touch the core of business innovation.