In its early days, Hadoop was chosen because it was much cheaper to store large amount of data, compared to Enterprise Data Warehouse . However, Hadoop required users to have strong technical background to be able to query or do anything on Hadoop. Therefore, the assumption was that Hadoop was only good for data storage.
Today, Hadoop is still the best option for inexpensive data storage. And the reality is as more technologies developed, Hadoop has become more and more user friendly too. In fact, the latest Big Data Maturity surveys indicate that in addition to the traditional data storage warehouse capability, a significant number of companies are using Hadoop for BI.
Companies like Yellow Pages are seeing sub-second BI query response time on Hadoop and have been able to drive increased Hadoop adoption across their organization. If driving Hadoop adoption has been a concern for you in the past, maybe you should reevaluate Hadoop for BI now.
Watch this 10-minute video with Chris Oshiro to understand:
- Why Hadoop is more than just an ETL machine
- Why just doing Data Science on Hadoop is not enough
- What Hadoop needs if it is to replace the Enterprise Data Warehouse
To learn more about Hadoop, check out these resources below:
- Customer Webinar: Yellow Pages: see How Yellow Pages does BI on Hadoop
- TECH Webinar: Increase Hadoop Adoption and Utilization: how to simplify the process of designing and building self-service interactive analytics
- Guide: 5 Things You Should Know About Hadoop: learn the top 5 key facts about Hadoop that influence Hadoop's capabilities within your organization.
Thank you for reading this blog, we hope this overview was valuable. If there are other questions you’d like us to address, feel free to comment below.
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