Unless you’ve been living under a rock for the last ten years, you have heard the term “big data.” Do you know what it means? If you’re like most people, you probably answered something to the effect of “kinda.” Well, let’s clear a few things up.
What’s the big deal with big data?
Companies of all types are adopting big data practices to improve their operational efficiency and better understand their customers’ needs and wants. Businesses properly leveraging big data see higher productivity and profits than their counterparts. The power of big data is no fallacy, and the trend has gone mainstream. In fact, 70% of enterprise organizations have either deployed or are planning to deploy big data-related projects and programs, according to the 2014 IDG Enterprise Big Data Research report.
What is big data?
It can be difficult to decipher the meaning of big data amidst the buzzwords and marketing speak. Big data is definitely big, but it is also misnamed, as Tom Davenport mentions in his new book, Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Big Data means different things to different people, but it can be generally defined as the following:
Data that is too large, unstructured and/or rapidly changing to store and analyze using traditional database management and analysis tools.
To better understand big data, the core characteristics are often referred to as the four V’s of big data: volume (size), velocity (speed of change), variety (lack of structure) and veracity (trustworthiness). Many have recently been adding a fifth V, value, to highlight the importance of obtaining value from the data.
Is bigger better?
With over 90% of all the data in the world having been generated in the last 2.5 years, there is no denying that big data is getting bigger. As our digital footprint rapidly increases, it is easy to get caught up in the quest to capture more and more data. While more data is often beneficial, in most cases additional data collection isn’t where organizations should be focusing their efforts. Prior to wanting more, ensure that you are making the best use of existing data. Are you successfully obtaining value from the data you already have? The value of your data does not lie in its volume – it lies in the use and reuse of it. So before making your big data even bigger, structure your existing data, analyze it, and ensure that you obtain value from it. Remember, your data is only as good as the insights you glean from it.
What is the biggest risk related to the adoption of big data?
Big data initiatives are costly. It is easy to become overwhelmed by the search for the right tools. The biggest threat that organizations face as they look to leverage big data lies in its general use and application. Companies need to spend more time thinking through the application of the data that is collected and analyzed. The majority of big data initiatives begin seeing their full ROI after 18 months. Preparation is key.
What is the “next big thing” in big data?
Many view real-time big data analytics as the next big thing. I disagree. I believe there is something much bigger. The ‘next big thing’ in big data is something that makes it easier to uncover the ‘the next big thing’. This involves getting answers to questions that would otherwise go unasked. Current big data analysis is too dependent on human intuition and initiation.
As Gurjeet Singh, Co-Founder and CEO of Ayasdi, states in his Fast Company article,
“Every Big Data exploration starts with human assumptions and biases that amount to an educated guess in the form of a query … with more larger and complex datasets, it is simply too difficult for the brain to make the connections that lead to making the optimal query.”
I believe Gurjeet is spot on, and I let him know that. There is too much reliance on asking the right questions. Automating the discovery of insight through advances in data-led discovery is the next big thing in big data. This will empower businesses to better attack big data analytics from both ends, targeted high-value questions and data-led discovery. Some of the biggest problems have solutions that are buried in data. This breakthrough in big data technology will allow us to begin finding valuable answers to questions we didn’t know to ask in the first place.
