Noodling on NoSQL: Thoughts on Multi-Structured Data Management
FEB 20, 2014 4:18pm ET

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Is There a Place for NoSQL in BI and Analytics?

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A question I receive quite a bit from people who are newly introduced to NoSQL platforms and the overall concept of multi-structured data sets is the following:

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Comments (7)
John,

Thanks for an excellent article. I agree, the most important thing is the question. This applies not only to connecting to NoSQL or Hadoop but also why you decide on a particular architecture in the first place. So it comes down to not what toy is the shiniest of newest but what helps you answer the questions that the business is asking over the long term.

I also want to amplify another point you bring up--"For advanced analytical practices, whether the data is structured or multi-structured, you often need to prepare the data for analytical models - so there is no reason that you cannot use multi-structured."

I would say that this is true for any type of analytics/data exploration/business intelligence/slice and dice/. --the vehicle that we are using to make sense of the data has its own input requirements. For example, Business Objects was originally designed to go against a RDBMS. As the need emerged it needed go against a cube structure.

So I view the problem of BI or Data Visualization tools going against a new architecture. The broader question is, how do I access and modify the data in a particular source to conform with the requirements of the tool that I need to answer the business question.

Posted by | Friday, February 21 2014 at 11:28AM ET
John, Thanks for an excellent article. I agree, the most important thing is the question. This applies not only to connecting to NoSQL or Hadoop but also why you decide on a particular architecture in the first place. So it comes down to not what toy is the shiniest of newest but what helps you answer the questions that the business is asking over the long term.

I also want to amplify another point you bring up--"For advanced analytical practices, whether the data is structured or multi-structured, you often need to prepare the data for analytical models - so there is no reason that you cannot use multi-structured."

I would say that this is true for any type of analytics/data exploration/business intelligence/slice and dice/. --the vehicle that we are using to make sense of the data has its own input requirements. For example, Business Objects was originally designed to go against a RDBMS. As the need emerged it needed go against a cube structure.

So I view the problem of BI or Data Visualization tools going against a new architecture. The broader question is, how do I access and modify the data in a particular source to conform with the requirements of the tool that I need to answer the business question. | Friday, February 21 2014 at 11:28AM ET

Posted by | Friday, February 21 2014 at 11:43AM ET
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