Hot? Warm? Cold? Which Data Should You Move to Hadoop?

Today’s enterprises are challenged with capturing large amounts of data from a number of sources in a variety of formats, and then storing it in a cost-effective, timely manner in their data warehouse, the cloud and Hadoop. But how do you know that you’re moving the right data to the right place? Which data is hot, which is not, and what does that mean to where it should be? Find out in this blog post.

Today’s enterprises are challenged with capturing large amounts of data from a number of sources in a variety of formats, and then storing it in a cost-effective, timely manner in their data warehouse, the cloud and Hadoop. But how do you know that you’re moving the right data to the right place? Which data is hot, which is not, and what does that mean to where it should be?

A large gaming company is able to advertise paid downloadable content while a person is playing the game, knowing that the advertised offer has statistically the best chance for a sale based on what the person is doing right now in the game combined with the historical insights on gameplay behavior and responses to past offers.

Is this scenario using hot, warm or cold data? A combination of all three? Join us and find out!

On June 23rd at 10 AM PDT/1 PM EDT, Rodan Zadeh and I will be hosting a live webinar in which we’ll explain how to:

  • Take your data’s temperature to determine what is cold, what is warm and what is hot
  • Rebalance your data warehouse to identify less-frequently accessed data and resource-intensive workloads that can be moved to Hadoop
  • Seamlessly integrate your current enterprise data warehouse with a Modern Data Architecture
  • Develop a roadmap for implementing Data Lake that includes operational and analytical data sets
  • Use tools like Apache Drill to perform secure, concurrent, low latency SQL analytics on big data
  • Better utilize data assets to reduce costs while realizing more value
 

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