The term ‘Big Data’ is used to describe the huge amounts of data that inundate businesses on a day-to-day basis, whether this data is structured or otherwise. Data volume, however, is not as important as what companies actually do with it. For instance, big data can be pored over and analyzed to glean the kinds of insights that can lead to more informed decision-making.

Used correctly, in fact, Big Data can be used to track things like spread of disease much faster than more ‘traditional’ methods. Google was able to track the spread of Flu (with varying degrees of success) much faster than the CDC, around two weeks faster in fact, by tapping into the large amounts of data generated by search results.

Crazyarts / Google data used to track spread of flu – Pixabay

It is this kind of data analytics that can help drive businesses and organisations forward. A business or individual can take an amount of data from just about any source and analyze it in order to find the solutions and trends that will help your business to:

  • Reduce costs
  • Streamline operations
  • Develop new products and services
  • Make smarter decisions

Big data combined with highly efficient and powerful analytics can be a tremendous boost for any business and can help to find root causes of setbacks and failures, discover customer buying habits and determine next steps to boost sales further and even discover fraudulent behaviour within the organization itself.

That being said, stored data is only as useful as the measures taken to ensure the integrity of the data, not to mention its security. This has become more of an issue in recent years, and there are several steps that can be taken in this direction to ensure data integrity compliance.

Who uses big data

It isn’t just search giants that make use of big data, although they can make use of it to great effect. Governments, retail outlets, manufacturing companies and financial institutions, to name just a few, also find great value in analyzing large volumes of data sets.

Manufacturers, for example, fully armed with the kinds of insights that big data can provide them with are able to boost productivity and improve the quality of their products. Even waste management within manufacturing industries can be improved upon thanks to proper analyzing of collected data.

As analytical tools become more powerful and enter into common usage, more and more companies are making use of them. This adoption of SaaS technology means that companies are able to solve problems faster than before and can make business decisions that are better informed and they can make them in a shorter time and with less deliberation.

Big data in the entertainment industry

Much was made of the magic sauce that Netflix uses in its algorithms that are able to predict what its subscribers would like to watch next. Netflix themselves played their cards very close to their chests, and still do, and the rest of us were left wondering just how they managed to do it and so accurately.

Today it is not so much of a mystery, and it is something that others are doing now too – although perhaps not with the same levels of accuracy, at least not in these types of predictions since personal taste is so subjective.

Netflix was just ahead of the curve in terms of harnessing big data and being able to analyze it in order to judge what their subscribers’ individual viewing tastes were. This, in turn, led to IP acquisitions that perhaps would not have been made before, providing subscribers with the types of new shows that they actually want to see.

By collating large volumes of data and making use of high-powered analytics, Netflix very quickly became a global phenomenon.

Big data is important for many different business types, and in a world dominated by business and service provider competitiveness, collating and analyzing that data is becoming more and more important.