Cutting through the data fog

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I’m borrowing from Charles Dickens here, but the vast expanse of data available to us can feel overwhelming at times, and the challenge of interpreting it like wading through the foggy landscape he once described in Bleak House. As data analysts, we are required to make the most of the data we have in our organisations, and to find a route through to the insights that lay within.

The MRS conference on analytics earlier this year highlighted the vast range of analytic approaches being adopted across the industry. Regardless of the approach we may take, what struck me most is our collective reliance on connecting different data to add deeper analytic value. Whether it be traditional modelling – for example, linking weather data to the adoption of a brand or applying social data as a determinant of consumer behaviour – at the core of all of this is the principle of connecting data to create better analytic findings.  

While data connectivity is not new, there is an important opportunity for analysts to think about the concept of this connectivity in a different way – moving away from standard, one-off solutions towards continuous connectivity, to give a more seamless and ‘always-on’ analytic approach. This requires us to be open, however – to new approaches, ideas and partners, and to outside solutions and data sets – so we can be focused on the greater good and the best possible solutions for our clients.  

My own experience of this thinking came when working in the digital industry, where openness across agencies created new measurement approaches that are now adopted across the media industry. This collaborative approach was refreshing, and a departure from that of the traditional market research world.  

Datasets can operate in isolation – that we know – but where data connects is where we can build value and deliver greater insights to help shape our business, and that of our clients. 

An increasing number of organisations are focused on adopting this way of working and, specifically, on how continuous data integration can help them automate to move more quickly and to differentiate themselves. 

Application programming interfaces (APIs) are now just the start of the conversation, as businesses – such as us here at Nielsen – are investing in developing the necessary pipes to create networks that connect disparate internal data sets to third-party data. 

Our focus is firmly on opening our ecosystem and making our data available to partners, and we’re doing this in three ways. Firstly, we’re opening up and integrating our internal data sets to make our services even more useful and relevant to our clients. Secondly, we’re opening up our data to our clients, so they can integrate and connect it into their own data networks. Finally, we’re making our data available to other businesses, start-ups and developers, so we can connect and work together on new and innovative applications for clients. 

Being open isn’t always easy, but we firmly believe that, where there is nervousness, we need to dust off the non-disclosure agreements to provide the cover for this new way of thinking – and, at worst, we walk away, but with the knowledge that we have tried.

Data is everywhere. As our individual behaviours leave an ever-expanding data footprint, our challenge is to think bigger about how we can work together in the spirit of openness and collaboration to advance the abilities of our industry – to cut through the fog and push the traditional boundaries of analytics. 

Connected data approaches lead to faster, smarter and more coordinated decision-making. Given the complexity of the data pool available today, connectivity needs to be at the heart of any data strategy – and simplification should be the guiding principle to achieving it.