Big Data in The Digital Age
Matt Potts
By Matt Potts
Blog

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Big Data is another hot topic for organisations this year (at all levels and lines of business) and many people consider Big Data as the new term for Business Intelligence.

 

There’s many good definitions around what Big Data is, and isn’t, but what does it actually mean in terms of change for organisations and their adoption of the Big Data movement, along with the ways they’ll need to adapt their processes to both embrace it and take advantage of it.

Below are the 9 key areas of Big Data along with some summaries:

Figure 1

Now

Big Data is a here and now issue, the amount of stored information grows four times faster than the world economy and the processing power of computers grows nine times faster. We are being whiplashed by these changes but are we are in a position to manage and more importantly take advantage of this. We need to let the data do the talking and allow it to help us make connections that we never thought existed.

Complete

This is about us going from using some of the data to using all of the data. The ease at which we can now collect, process and analyse vast amounts of data means the concept of sampling isn’t required. This helps us drill and create subsets at whatever level required, also enabling us to generate 2nd+ uses of the data (see sections on Use and Capture).

Messy

Use all available data. With a very large dataset, when compared to a small one, reducing the errors isn’t necessarily as important because they don’t get amplified within a larger set. A Big Data mind-set will require us to reassess our views on exactitude. With Big Data we will be satisfied with the general sense of direction rather than knowing everything down to the penny.

Association

Predictive Analysis will really shine in the Big Data age as will the ability to spot strong correlations between data values when we can compare all of the data sets. Have you ever overlaid your sales data with weather data to see if there is any correlation? With small or non-full data sets, we may need to draw conclusions and theories at data, but with all data the data tells the picture.

Capture

We can now “datafy” anything that is relevant to our business: numbers, words, locations, interactions. Through a range of sensory and data capture technologies we have the ability to catch every piece of data we want and at huge scale. We need to see the world as information. Another point here is that we may not know the value of the data that we collect until a future point in time when it can then be realised, but the fact that it may not be used until the future shouldn’t necessarily stop us from collecting it. This requires a mind-set to say “what if we collected this data?”

Uses

With Big Data the value of data is changing. Data can shift between having a primary use to potentially a wide range of future uses. Data isn’t a consumable and can be used many different times for different purposes. Data needs to be considered in all of the ways it could be deployed in the future not just the present.

Networked

Big Data has a value chain, and through collecting data there maybe instances where the data may be of particular interest to 3rd parties, therefore creating a new revenue stream (part of the Networked Economy). Where you may be collecting data that others aren’t this can place you in prime position for competitive advantage and innovation.

Risk

Business is still built on the foundations of great people with great ideas and the ability to execute them. Data will never be able to replace these elements and we do need to be conscious that we don’t move to an environment of dictatorship by data.

Regulation

They’ll still be the need for control, integrity and rules around data, including governing the ways we use data to predict future outcomes as well as ethics of what we collect and how we apply it.

 

Many of the above points will require lots of mind-set changes within organisations, including imagination and the technical skills involved – all adding up to a Big Data mind set and ethos.

To learn more or understand how Big Data can work for your organisation, along with help in building a business and technology roadmap to adopt and embrace it, please get in contact with us.

Matt Potts
By Matt Potts

Matt Potts is Solution Principal for Business Insights, specialising in Business Intelligence and Analytics. Matt has worked in the BI domain for over 8 years, helping organisations turn their data into actionable business insights through the use of agile BI platforms and delivery models. He is involved with multiple clients across varying lines of business and industries, working with them to ensure they realise the value from their investment in BI technologies. Outside of work Matt enjoys running, cycling and watching a range of sports and is kept busy by DIY projects at home.

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