Disruptive technology explained – Big Data

Disruptive technology explained – Big Data

From the AiM Next Generation Technologies team.

What is Big Data?

I have a paper-based address book. It contains many names, and limited information about each person, e.g. address and telephone number. If I were to digitise this, I’d get a table with many rows (each entry) and a few columns (name, address etc.). My online address book, used for composing emails, contains a few more rows, since it’s easier to accumulate contacts online, and each row has more columns, with email address, personal and business phone numbers and sometimes other salient facts, e.g. birthday, children’s names. All useful information, that I’ve stored for a reason.

In fact, it’s very easy to gather and store information electronically, a children’s nursery might have the names of all the children in their care, parents, carers, other contacts, addresses, ages, photographs, doctors’ details, medical details and dietary requirements. Going to an extreme, a mobile phone provider might store not just personal details, phone and text data, but also associated information, for instance geolocation data, billing data, use of the personal pages on the providers website etc.; the list is endless.

In the case of my address book and the nursery’s database, data is generally stored in a table or database, whereas the telephone company may store many different types of data in many different ways.

The data I have is limited, the data the mobile phone company has is big, very big; hence the term, big data. However, ‘big’ is a relative term, in the early 2000’s a terabyte of data was ‘big’, now it’s petabytes, and what’s ‘big’ for one company may be small for another. Linking all these, is the concept of large volumes of data that are useful and can be used to provide meaningful analytics for an organisation, for example, point of sale coupons based on buying habits, or real-time fault detection.


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