As data and applications move to the cloud, the conventional wisdom is that data warehousing is dead. Yet this may not be true.
Data warehouses are changing with the times and are reaching for common ground with the cloud.
Researcher Dave Stodder reports on how companies are trying to maximize the utility of data warehouses in this article from TWDI Upside:
From the beginning of the Hadoop revolution, some business and IT leaders saw data lakes based on Hadoop (and more recently, Spark) clusters as potential replacements for traditional data warehouses that they deemed too limited in scale, performance, and scope to handle the big data tsunami, at least for the right price. Other organizations wanted to retain their traditional data warehouses to support existing BI and analytics workloads but develop and deploy data lakes and hubs to handle new data science and advanced analytics workloads. In other words, they preferred to augment their data warehouse by building out a multiplatform architecture.
TDWI recently surveyed organizations about their plans to augment or replace existing data warehouses (the full research will be published in an upcoming Best Practices Report). We found that the majority of organizations do not want to stand pat; about two-thirds (65 percent) of the 232 organizations surveyed want to either augment or replace their existing data warehouse with technology solutions centered on a data lake or hub built with on-premises Hadoop or Spark clusters or systems based in (or native to) the cloud.
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Data warehousing is not dead, but it is changing as new technologies — running the gamut from scalable, high-performance platforms and better development and administration tools to AI and machine learning — have their impact. The challenge will be to embrace the new technologies and cloud services and position the data warehouse for optimal benefit.
