I've heard so many big data vendors bash data warehouses as a way to justify their new technologies that it's getting annoying. To them, data warehouse systems are monolithic, costly and inflexible, while their technologies are fast, flexible and affordable. "Buy our products," they shout in their shiny collateral, "and we'll save you from data warehousing hell."
As if technology were the problem. Or the solution.
I'll admit there are plenty of data warehousing failures out there. Designing a data warehouse is not easy, and implementing one is even harder. The critics are right -- data warehouses take a long time to build, cost a lot of money and are hard to change. But that doesn't mean we should ditch them.
At its heart, a data warehouse is not a technology or tool. It is primarily a business process that unites an organization in electronic form (i.e., through data) so it can function as a single entity, not a conglomeration of loosely coupled fiefdoms. Without a data warehouse, business executives run blind, making critical decisions with inaccurate dataor no data at all.
Although you need technology to implement data warehouses, technology can't harmonize business perceptions and deliver an enterprise view of an organization. Only business people can do that. In fact, getting business people to agree on the definitions of core business entities can be more challenging and time-consuming than creating the technical infrastructure. Instead of blaming technology or technologists for poorly designed or under-performing data warehouses, we should point the finger at executives who fail to provide sufficient leadership, vision and patience to create a common data vocabulary for doing business.