If a data lake isn’t a data warehouse, as I proposed in my last post, then it behooves us to better understand more about this “new” data lake structure. In the fifth and final post in this series titled, Big Data Cheat Sheet on Hadoop, we’ll highlight some of the
In this 5-part blog series on the Big Data Cheat Sheet on Hadoop, we’re taking a look at these five questions from the perspective of a marketer: What can Hadoop do that my data warehouse can’t? Why do we need Hadoop if we’re not doing big data? Is Hadoop enterprise-ready? Isn’t
In response to my last post—Marketers ask: Why do we need Hadoop if we’re not doing big data?—a Twitter follower asked this question: It’s a fair question. Typically, marketers are more interested in the car (in this case, big data) than they are in the engine (Hadoop). But Hadoop is
"Our corporate data is growing at a rate of 27% each year and we expect that to increase. It’s just getting too expensive to extend and maintain our data warehouse.” “Don’t talk to us about our ‘big’ data. We’re having enough trouble getting our ‘small’ data processed and analyzed in
Recently, I was given the opportunity to present a session titled, An Executive’s Cheat Sheet on Hadoop, the Enterprise Data Warehouse and the Data Lake at the SAS Global Forum Executive Conference. During this standing-room only session, I addressed these five questions: What can Hadoop do that my data warehouse can’t?
