Big Time — Elements of Data Size in Scaling

I’ve run into additional questions about scalability.  It is significant to understand the concept in terms of assessing software against data size, since there are actually various aspect of approaching the issue.

Unlike situations where data is already sorted and structured as part of the core functionality of the software service being provided, this is in dealing in an environment where there are many third-party software “tools” that put data into proprietary silos.  These act as barriers to optimizing data use and gaining corporate intelligence.  The goal here is to apply in real terms the concept that the customers generating the data (or stakeholders who pay for the data) own the data and should have full use of it across domains.  In project management and corporate governance this is an essential capability.

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Do You Believe in Magic? — Big Data, Buzz Phrases, and Keeping Feet Planted Firmly on the Ground

My alternative title for this post was “Money for Nothing,” which is along the same lines.  I have been engaged in discussions regarding Big Data, which has become a bit of a buzz phrase of late in both business and government.  Under the current drive to maximize the value of existing data, every data source, stream, lake, and repository (and the list goes on) has been subsumed by this concept.  So, at the risk of being a killjoy, let me point out that not all large collections of data is “Big Data.”  Furthermore, once a category of data gets tagged as Big Data, the further one seems to depart from the world of reality in determining how to approach and use the data.  So for of you who find yourself in this situation, let’s take a collective deep breath and engage our critical thinking skills.

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