Topics: Big Data
Why do relatively few companies have success with big data?
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By: Steve Dine and David Crolene
Each year, we reflect upon the business intelligence industry and enterprise information management (EIM) industry and provide a review of the noteworthy trends that we encounter in the field. Our review emanates from five sources: our customers, industry conferences, articles, social media, and software vendors. This year has proved to be an interesting one on many fronts. Here is our business intelligence industry review and observations for 2013 and predicted trends for the remainder of 2014.
If the concept of a data lake is confusing to you, don't worry because you're not alone. A primary reason for this confusion is that the definition of a data lake seems to change depending on which constituency you ask. The big data community will define it as a central location for all your disparate data sources stored in its native format in Hadoop. Even within the big data community, it may be called something different, like enterprise data hub, depending on the vendor you're speaking with. In the Business Intelligence community, a data lake is defined as a staging area, or landing area, for your source system data. They make less of a distinction about where the data is stored.
The two questions I'm asked most often include:
1. If I build a data lake, does it need to be in Hadoop?
2. Is there any value in building a data lake?