Extending Your Data Warehouse Environment with Hadoop: Bringing Enterprise and External Data Together
TDWI Speaker: Philip Russom, Senior Research Director for Data Management
Date: Tuesday, February 27, 2018
Time:7:00 a.m. PT, 10:00 a.m. ET
Surveys run by TDWI show that roughly a fifth of mature data warehouse environments now include Hadoop in production. Hadoop is becoming entrenched in warehousing because it can improve many components of the data warehouse architecture—from data ingestion to analytics processing to archiving—all at scale with a reasonable price.
As data itself continues to grow and evolve, so do the use cases for Hadoop. For example, the first thing most data warehouse professionals do with Hadoop is use it for data landing and staging; this use case has recently evolved to address a broader range of data ingestion, including streaming data from machines, social media, the Internet of Things (IoT), and other external data sources. As another example, the data lake, usually deployed atop a Hadoop cluster, consolidates data from many sources—whether traditional enterprise apps or modern cloud-based ones—to enable broad data exploration and discovery-oriented analytics. As yet another example, data professionals often begin with structured data (though at scale) on Hadoop, then additionally tap Hadoop’s ability to store and process data of many structures—or no structure. Finally, Hadoop’s use is growing outside of data warehousing, as in multichannel marketing, the digital supply chain, data archiving, and content management.
Attend this webinar to learn about these and other ways Hadoop is being used in conjunction with data warehousing. All are meaningful because they help user organizations get greater business value from a widening range of data types, sources, structures, interfaces, and containers.
Philip Russom, Ph.D.