The concept of big data – the notion that we are overwhelmed by a flood of digital information like nothing we’ve seen before – holds both promise and peril. The allure is centered on the benefits that big data will bring, in areas from medicine to traffic to agriculture. These benefits will translate into profits for companies that manage, transmit, and store all that data.
Then there’s the other side: that big data will lead to privacy intrusions, lack of freedom, and, from a very practical standpoint, yet another headache for executives and IT managers. We have covered this topic in the past (see a great description of how automated demand response firms are focusing on data analytics or click here to read more about framing the problem for building operators) and our recent webinar, Innovations in Smart Building Data Analytics, also presented some excellent examples of how industry leaders are using data analytics for their customers.
The Three Vs
Many definitions of big data are available, but the most compelling framework was created by Doug Laney in a 2001 research report. This description focuses on three prime elements: volume, velocity, and variety. Volume refers to the bigness of the data – there are more sensors and signals than ever before, pumping out data on everything from location to temperature to transactions. Velocity addresses the speed that the data is being created, from subsecond phasor measurement unit (PMU) data describing the power quality on the grid to the rate at which Facebook is gathering our likes. (It should be noted that one overlooked aspect of velocity is not just speed, but also direction. Data is streaming not just from our devices, but also to servers, corporate analytics processors, and back to customers, all over the world.) Lastly, there is variety, which is the real game-changer. Data has never been unitary, and the diversity of data forms, standards, protocols, and utilities is growing by the day. While often presented as separate concepts, these three elements are intrinsically linked. I’d like to present the three Vs as a nested hierarchy (see below).
The 3 Elements of Big Data
(Source: Navigant Research)
Data volume gets most of the attention (hence the name big data, not fast data or diverse data) and velocity gets the communication and IT folks excited. But it’s the variety of the data, and the variety of the velocity and the variety of the volume, that makes the big data interesting. It’s not just that data is big or fast; it’s the diversity of speeds and directions that data travels to its many users.
Big Data, Big Challenges
For example, utilities used to report monthly electricity usage; now customers can see how much power they use every 15 minutes – that’s three orders of magnitude difference! In addition, utility data is now being served to customers, local grid operators, energy efficiency firms, and facility managers. Lastly, it is the complexity of the variety (the variety of the variety) that creates challenges, as well. For example, in the developing world, buildings are at many different levels of IT sophistication and electrical grids have to integrate old equipment and management processes along with new state-of-the-art high-tech factories that need highly reliable power.
So how is big data actually affecting cleantech markets and technologies? Going forward, in our research and our blogs, we will touch on how big data is changing cities and how it’s being integrated into regular business practices. We will explore how traditional firms are coming up to speed, while startups are using it to leapfrog their competition. We’ll also examine how big data is providing new opportunities and challenges to the cleantech markets and how those markets are responding.
Tags: Big Data, Building Systems, Digital Utility Strategies, Energy Management, Smart Buildings Program, Smart grids
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