Big Data Alone Is Useless

Advanced Analytics is Needed to Bring Insight & Value to Big Data


The Gartner Hype Cycles are published every July and August. Hype Cycles provide an overview of the relative maturity of technologies, services and business disciplines in a certain domain. They are useful to firms in that they help to determine when it’s appropriate to adopt a new technology, and give us some idea of which technologies actually survive market hype and could become a part of our daily life.

This year’s Hype Cycles saw Gartner make the potentially controversial decision to drop ’Big Data’ in favor of Advanced Analytics and Data Science.

The speed of Big Data’s fall from the list has been surprising. According to Gartner, Big Data has now officially passed the ‘peak of inflated expectations’, and is now heading into what it calls the ‘trough of disillusionment’. They claimed that they already have consistency in the way we approach the technology, and most new advances are additive or complementary rather than revolutionary.

Betsy Burton, the Gartner analyst who authored the report, explained the decision: ‘There’s a couple of really important changes. We’ve retired the Big Data hype cycle. I know some clients may be really surprised by that because the Big Data hype cycle was a really important one for many years. But what’s happening is that big data has quickly moved over the Peak of Inflated Expectations and has become prevalent in our lives across many hype cycles. So Big Data has become a part of many hype cycles.’

This does not mean that Big Data is going to disappear, it has simply become so established that it is no longer a question of whether or not it is hyped. Gartner has broken the various topics that formerly encompassed Big Data into other areas. These include Advanced Analytics and Data Science, Business Intelligence and Analytics, Enterprise Information Management, In-Memory Computing Technology, and Information Infrastructure.

The inclusion of Advanced Analytics is telling. Advanced analytics is necessary to create value from data. While basic analytics can give businesses a general summary of the data, advanced analytics offers far deeper data knowledge and granular data analysis that can be a powerful tool in decision making processes.

Advanced analytics is the fastest-growing segment of the business intelligence (BI) and analytics software market, and surpassed $1 billion in 2013. However, many companies are still not properly utilizing it. That it’s considered ‘hype’ while Big Data is now an established fact seems to suggest that many companies are just aimlessly collecting data to no apparent end. Advanced analytics is necessary to convert the deluge of information into actionable real time insights. Advanced analytics requires a range of talents, including data integration and preparation, data mining, and intelligent algorithms. It also requires investment and knowledge across the industry. Without it though, you can collect all the data in the world and it will be completely useless.


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