Implementing Big Data: Pitfalls and Essentials

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Over 90% of all the data in the world, since time began, has been created in the past 2 years. Just the gargantuan size of it is intimidating to venture an implementation.


One of the biggest challenges for managers has been making decisions based on data analytics. They have to take into consideration the ‘cleanliness’ of the data, the ‘timeliness’ of it and the accuracy of the analysis. 

Data that has been tampered with or assimilated from dubious sources can throw up entirely incorrect analysis and point n the wrong direction. Outdated data is useless for making real-time or projected decisions. And finally, the quality of the analysis plays a major role in the decisions that will guide the business in the direction of success.
 
Managers had just begun to get their heads around analytics of simple knowledge bases, and the business world was just getting into the groove of working with it, when things changed radically. Big Data showed up and altered the way in which data can be used in a business.

Big Data Application
In the erstwhile application of data, there was first a business plan and then data analytics was used as an enabling tool to achieve that plan. Big data has flipped that scenario on its head. It has the capacity to derive innovative opportunities that can enable businesses to create a business case; and then help in achieving it. This is a radical concept that businesses need to comprehend, to utilize the full potential of big data.
 
Pitfalls when Implementing Big Data:

  1. The innovations on technology related to big data is evolving rapidly. This can delay the decision to embrace it, while waiting for the next innovation. Don’t procrastinate. Get into it and grow with the technology, it will give you a leading edge in understanding how to wield its power. Don’t be overwhelmed by the amount and speed of change.
  2. Applying and wasting big data, by using it like conventional data. Be sure you are ready to use it as a game changer and not just a larger version of conventional data analytics.
  3. Too much focus on technology and tools. Getting swayed by companies that claim to know all about Big Data and its technology. Yes, they know more than you. No, they don’t know it all as its also new for them. They too are learning as they sell. So be prudent. Match your requirement to the technology you acquire. But even more important is to align the employees to the concept and utility of big data even as the investment is made. Without their active participation it’ll be very difficult to get a big data project off the ground.

 
Essential when Implementing Big Data

  1. Business must closely collaborate with IT if big data is to be successfully implemented. This will take away any probability of a mismatch of expectations. The technology acquired by IT will be in congruence with the requirements of the business.
  2. The expectations set by the business will be tempered with sound inputs from what the technology can deliver in a phased manner. Just acquiring a big data tool does not guarantee optimal output from day one.

Reminders:

  • Big Data is not a shortcut to success.
  • It is not a magic wand that will make every wrong right.
  • It is not a silver bullet for your business.
  • It is an opportunity to understand better about your business, so you can make the right decisions.

The important thing to remember is that Big Data is just a whole lot of data if you don’t know what to do with it. To put it in perspective – Google alone processes over 40,000 search queries per second, making it over 3.5 billion queries in a day. There should be clarity on what you want from your big data. You have to ask the right questions.
 
Big Data is the conduit between data and decision-making. 

Republished with author's permission from original post.

Sunil Panikker
Sunil Panikker is a business consultant specializing in customer service, operations and business strategy. He has honed his expertise over 30 years of experience, working in senior management positions, with companies having global footprints, and responsibilities that have been cross-functional & multi-locational. His blog shares the experience and expertise assimilated from managing customer experience across multiple diverse industries.

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