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8 keys to make most of your Big data

Written by Anurag | Aug 4, 2016 6:30:00 PM

Big data technologies and practices are moving quickly. More and more companies are now realising the power of data and the fact is that a majority of businesses are adopting big data practices. But many of them, although put a lot of effort in collecting and analysing data, are not getting the desired results out of it.

So how can businesses put their data to the best use? Following are eight ways to make the most of your data - 

Treat your data pool as a treasure- Take advantage of all the valuable data that you own. Being the first step in your Big Data journey, a lot of attention is needed at the time of data mining. You need to distinguish what's important and what’s not.

Be real time- The data warehouse, is history. The most valuable data will be that which is collected and analyzed during the customer interaction in real time, not the review afterward. In the digital economy, interactions will occur in near real-time. So the data should also be captured and analysed in real time.

Capture all that matters with no miss outs- Analytics is all about figures and may go entirely vague if you miss out important information. Make sure you capture everything that can influence the customer’s experience and behavior, leaving no stones unturned.

Remember quality matters not quantity- Your analytics solutions should never be fed with junk. Ensure to utilise the right data for analysis. Always focus on the data that matters the most.

Explore new ways to generate more useful data- It's important to keep your data flow continuous. Find out ways to generate more customer data and keep it running so that your analytics tool always has a good supply of data to work upon.

The cost and efforts should be justified -  Best approach here would be to treat business data as your a key investment and justify the costs with the tangible benefits your data can offer. Focus should be to organise your big data efforts more effectively and save on costs.

Be agile - Being agile with your data and handling it in continuous and real time manner will make your data capable of dynamically constructing and managing any numbers of data views to satisfy the user observation requirements.

Incorporate learning into the business - The main reason we capture and analyse data is to ensure better decision making into the business. Hence it's important to ensure the analytics results are put to their best use and it leads to better business decisions and subsequently better business actions.