How can businesses use big data effectively

| | Data
Sherin Ratcliffe

Firstly, what is big data? Put simply, it is the search for commercially valuable insight hidden in repositories of data. These repositories can be vast. The data is usually so voluminous that it needs to be split into manageable chunks.

So how can businesses use big data effectively?

Finding links amongst the myriad segments of customer data could be the gold dust to bring sparkle to your career – or a monumental waste of time. Businesses are realising that by adding a stream of new data, or finding patterns in existing data, it is possible to enjoy a step change in performance. This is the ethos of “big data”.

Netflix used big data to forecast the success of House of Cards, starring Kevin Spacey. Netflix crunched the viewing habits of more than 30 million subscribers, using information such as viewing figures of similar series, the popularity of Kevin Spacey and the fall-off rate of viewers through a series, to draw conclusions on the probable viewing figures for House of Cards. Big Data justified the $100m budget for 13 shows. The approach worked. House of Cards became the most watched Netflix show in every country where the online media provider operates and the first online-only show to win an Emmy.

Data Discovery

Successful discovery requires building a data advantage by pulling in relevant data sets from both within and outside the company. Relying on mass analysis of this data, however, is often a recipe for failure. Analytics leaders take the time to develop ‘destination thinking,’ which is writing down in simple sentences, the business problems they want to solve or questions they want answered. Businesses need to ask very specific questions. Usually, data scientists within the business discover whether the question can be answered, these need to go beyond broad goals such as ‘increase wallet share’ and get down to a level of specificity that is meaningful.

To pull this data together, there are numerous big data solutions such as Kognitio however in isolation provide little value to an organisation unless that data can be acted upon to support the decision-making process. A valuable characteristic of big data is that it contains more patterns and interesting anomalies than ‘small’ data. Thus, organisations can gain greater value by mining larger data volumes than small ones.

Get Technical – Data Staging

Start small, it is much easier for a person to learn to be a data scientist than to teach a data scientist to understand your business. To help, use big data tools as a staging area for unstructured and semi-structured data before loading it into a data system. The big data system maintains all of the detail-level data while lightly-summarised data sets are made available to the analytics layer.

Use a Data Analytics Solution

A solution such as, Qlik fits naturally as either a direct recipient of the data from Kognitio or other Big Data systems. Big Data’s value can be unleashed for business users by condensing it and intelligently presenting only what is relevant and contextual to the problem at hand. For example, an executive might be interested in summary data across the company’s product lines, while a manager of a specific product or geography might need more detail, but only for the areas that he or she oversees. Qlik simplicity in terms of joining data from multiple sources for the purpose of associative analytics is very much evident.

To learn more and consolidate relevant data from multiple sources, get in touch with the Blueberry Wave to find out how we can help.

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