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Making the Shift from Big to Broad Data

May 03, 2012

In my previous post, I laid out why I think we need to move beyond the hype of Big Data technology and “bigness” to focus instead on the breadth and diversity of data, as well as signal extraction, analytics and deep insights from that broad data. 

Here we’ll delve into what we mean by "Broad Data" as well as some of the fundamental changes for businesses in today’s marketplace that compel the need to focus on breadth of data and on data stitching from disparate sources.

The shift of control to the edge of the enterprise

Social, mobile and cloud influences have caused enterprises to undergo a tectonic shift in how they do business with customers. The real value for an enterprise - the interaction with end users (customers) - has shifted one or two tiers away from the enterprise.  The control is shifting to social networks where people are talking about companies and products; to business networks where interactions are happening through partner channels; and to apps and the APIs they leverage.

The landscape for customer interaction with enterprises looked significantly different just a few years ago than it looks today. Data was controlled within the enterprise – all of the data that an enterprise gathered were collected when partners and customers interacted with systems produced and provided by the enterprise.

But today’s landscape reveals an expansion of the interaction with customers by one or two degrees from the core of the enterprise. The evolution of the apps and API economy has resulted in people using apps that may or may not have been created by the enterprise. Apps then are the vehicles that inform the enterprise about how customers and partners are interacting with them.

Factor in the influence of social networks, partner- and business- networks and the effect is amplified. Simply put, the enterprise is no longer in control of the data it needs to inform and make accurate business decisions. That’s the fundamental shift of interaction to the edge (and even beyond the boundaries) of the enterprise.

This shift in the market has a fundamental implication for the Big Data conversation. The number and variety of data sources is much more important than the volume that comes from any one source.

Big Data becomes Broad Data

Data is not by itself "Big". Aggregated fragments of small and contextually related data make for "Big" - more accurately - "Broad" data. Taking advantage of the breadth of the data, its variety, its dynamism, and its disparate sources is the real future.

Just a few years ago, the data an enterprise collected were collected from physical stores, Web sites, and partners and from 5 to 7 primary data sources. Data from point-of-sales data sources, supply records, customer records, warehousing records, and so on reflected all the interesting things happening with respect to an enterprise’s interaction with customers and partners.

Today the sources and types of data are expanding continuously - there are hundreds of new data sources, each generating data (which might be small or not-so-small) and definitely generating a smaller signal/noise ratio.

The shift is significant - from 100% of data captured from 5 or 6 sources to a scenario in which maybe less than 50% comes from those original sources. In time, I contend that the old enterprise sources may not even be the most important source.

The many new sources are much smaller and from a variety of relatively new sources: from Twitter, Facebook, partners, tens and hundreds of apps, some built around your APIs. The list goes on. This essentially defines the need for the shift from the deep and big focus of the old world to the broad and pervasive focus of the new world. This will allow businesses to focus on all of the new places in which there is the potential of a signal relevant to their enterprise.

Whenever you collect lots of data, you of course collect lots of both signal and noise. Next time, we’ll look at increasing the signal to noise ratio of broad data - Big Broad Data: Increasing the signal to noise ratio »

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