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Big data architecture

So what is this “big data architecture” buzzword actually mean? This is simply the system that digests the huge quantities of raw data so ubiquitous in the modern marketplace and prepares it for big data business analytics. Big data architecture is therefore basically a blueprint for the big data business  analytics – big data for big analytics.

Big data architecture therefore needs to be structured to cope with a number of different categories of tasks:

  • Big data batch processing.
  • Big data real time processing.
  • Machine learning.

Big data, big analytics

A big data business, requires big data business analytics, that much is obvious. But big data analytics require properly designed big data architecture to be cost efficient and provide the optimal tools for making the right choices in a highly competitive business.  

The big data just keeps on getting bigger, as the amount of accessible for analysis rises on a daily basis. But getting the data is only the first and most easiest step. You also need to be able to form a coherent picture from these reams of information, and you need to be able to carry out the big analytics on this big data in a timely enough manner to actually make critical decisions on time. Big Data requires not only big analytics, but rapid big data business analytics.

Big data business

It has been said and said again that data is the new oil. So what kind of business model is right for all the big data businesses out there? As thousands of would be big data business startups littering the landscape beneath the social media success stories testify, there is no single big data business model which guarantees success. Still, quite a few well established companies remain committed to the vision of transforming themselves into competitive big data businesses, and capturing the associated revenue streams. Apple and Amazon are worth noting as well established and successful big data business companies that have generated entirely different big data business models, big data business analytics, and big data architecture to handle a very different flow business flow. The same is true for Netflix and Pandora. It seems like an inversion of the Anna Karenina Principle – failed big data businesses seem to be alike in latching on to a single big data business model, whereas all successful companies adopt a different unique data business model that is right for them, and for their value proposition.

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