A Clear View of What You Can Achieve with Big Data




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Big Data – what does it mean?  Ask 5 people, get 5 different answers as it means many different things to different people. I do believe in Big Data and the value that can be achieved as data driven decisions and applications create immense value by utilizing data sources to discover, present and operationalize important business insights.  However, what I am seeing in the marketplace is confusing as every tech company claims to have a solution for analyzing the huge amounts of data businesses create. I challenge this reality … Do these tech companies really know how to use this data?  Or are they jumping into the hype and creating what is now being dubbed “Hadumps” and “Data Swamps”?   

Here is my belief … data on its own is meaningless – period. The value of data is not the data itself – it is what you do with the data.  For data to be useful you first need to know what data you need, otherwise you just get tempted to know everything and that is not a strategy, it’s an act of desperation that is doomed to end in failure. Why go to all the time and trouble collecting data that you won’t or can’t use to deliver business insights? Focus on the things that matter the most otherwise you’ll drown in data. Data is a strategic asset but it’s only valuable if it’s used constructively and appropriately to deliver results.  

So where do you start?  While I think we can agree on the value of Big Data, there certainly is NO agreement on a standard approach on how to identify and frame a Big Data initiative.  What I have found time and time again, is that companies are focusing on the enabling underlying technology first whereas they should be focused on the business objectives FIRST.  After all, that is where the data comes from and that is where the value is – in the data.  There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that I’ve personally have observed is organizations that have a strong operating model stand apart. This operating model has very distinct elements, which includes a well-defined organizational structure, a systematic implementation plan, and strong leadership support.  To ensure success, there are distinct steps to successfully implement a Big Data engagement.  I recommend that you answer a few key questions first:

  • What is the initiative goal?
  • Once this goal is met, how will it change the business?
  • What are the obstacles to getting there?
  • Who are the key stakeholders and what are their roles?
  • What early outputs will tell me if the insights needed from the data are going to be extracted or not?

In summary, Big Data is all about asking the right questions, which requires business context, then iterating on your initiative as you learn which data sources are valuable, and which questions yield real insights. You don’t have to know the end from the beginning, but you should have a clear view of what you hope to achieve.  Big Data success flows from a cultural affinity for data, which can be sparked by a strong leader within an organization, but ultimately must become how an entire company thinks about its business.

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