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The 4 Steps To Big Data Success (Or How I Learned To Stop Worrying And Love Data Physics)

        posted by , November 20, 2012

What are the physics of the big data universe?

You've probably read anecdotal reports of the sweet business value that smart organizations have gleaned from big data.

If you want to understand the source of this value you should take a look at the physics of big data.

In the big data universe there are 4 principles of business value:

1. Volume

The reason that people like Facebook is that most of their family and friends are members. Let's say that only 5% of your friends were members of Facebook — it wouldn't be nearly so interesting.

That leads us to the first principle of big data:

Principle #1
The more data you have, the more valuable it is.


If a social network has only 10 members, each profile has virtually no value. A social network that's dealing with billions of accounts achieves more value per profile.


2. Variety

Big data solutions often combine data from many sources (both structured and unstructured).

Principle #2
Data from a variety of sources tends to be worth more.


A search engine is able to enhance the value of its search index by combining it with a variety of data from other sources. For example, GPS data from a mobile device allows a search engine to deliver localized search results to its customers.


3. Velocity

If a search engine took 4 days to return the results of a search it wouldn't be very popular. Search engines need to be rocket fast to achieve any value at all.

Principle #3
The faster you can process data, the more it's worth.



4. Quality

Let's say a social network had a problem with spammers and 30% of profiles were fake. The value of their profile data would drop dramatically.

Principle #4
The higher quality your data, the more valuable it is.



Implications For Your Business

When you build a business case for big data it's important to apply the fundamental economics of data.

You might be pleasantly surprised the business value that can be found when you improve the volume, variety, velocity and quality of your data.


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