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Big Data

Big Data seems to become Big Business. Why? The amount of data is growing exponentially over the years. The percentage unstructured data is getting each year a bigger piece from the data cake. What is Big Data and how can companies benefit from it. There is an adagium saying ‘Turn your data into dollars’ pointing out that an organization must do something with their data, in other words make profit from it. If this is the case with regular data, does it make sense for Big Data too?

What is Big data?

Big Data is often characterized by four V’s: volume, velocity, variety and variability.

  • Volume is about the amount of data.
  • Velocity is about the speed to which the data is coming to you and is hiding from your field of sight (streaming data like Twitter messages).
  • Variety has to do with the different formats the data is in (range of data types).
  • And variability is about the different meanings a data element can have (misspellings, synonyms).
As you can see the phrase ‘Big Data’ can be a little bit confusing, because it refers also to non-volume issues. Even if the data volume is relatively small, it is called Big Data when there are issues regarding velocity, variety or variability.

Is Big Data new?

From our point of view we would say yes, definitely. In previous times large databases were set-up to store a lot of structured (customer) data. But today, the amount of data is so huge and the diversity so immense, that some data can’t be stored in a regular relation database anymore. And if things can’t be stored in a database, we cannot analyze the data in a fashion manner. We need special methods, tools and software in order to be able to analyze Big Data in real-time or near real-time.

How to benefit from it?

The promise of Big Data is that the ‘big data’ hides valuable information about your clients behavior or what they are thinking. It can unravel important moves of your competitors which are not yet made public and it may contain significant trends about the market you are operating in. If you are able to analyze the huge amount of (streaming) data better and faster you will get deeper insights you didn’t had yesterday which can get you ahead of your competitors. We have made a list of twelve smart businesses who profit from Big Data.

What are typical Big Data sources?

Big Data can be extracted from the following data sources (some examples):

  • social media like Twitter and FaceBook;
  • sensors in machines or device measuring for example how well the device is functioning or the temperature;
  • sensors in the human body or other organism;
  • RFID tag sensors measuring product movements;
  • logs containing surfing behavior of your website visitors.
Often you need special adapters (API’s) to be able to extract the data.

What Big Data ‘solutions’ are available?

This is the most difficult question to answer because it depends on a variety of things. You can’t really speak about solutions when it comes to Big Data, because the challenge can be overwhelming complex

 

Download here the BI Software Survey where all Big data solutions are evaluated.