Big data had a big year in 2016. Several key trends emerged, some in line with predictions made at the beginning of the year and some representing unexpected developments. The fact of the matter is that 2016 was a good year for big data advocates. More uses were found for insights gleaned from performing in-depth analytics on gathered information, helping organizations understand that this is something they need to strategize around in order to remain competitive in their respective markets.
Now, as the year gets slowly smaller in the rear-view mirror, it's helpful to look back on some of the most important developments and see how they factor into the new year and future analytics strategies:
Big data isn't enough on its own to enact any real change in an organization – companies need the right kind of analytics tools to draw out insights so managers can implement the findings. In that regard, CIO contributor Thor Olavsrud reported at the end of December that one of the biggest trends for organizations across the world was to embrace big data analytics. In fact, research firm IDC found that the market for big data analytics has been expanding rapidly, such that in 2019 it's expected to be worth a total of $187 billion.
The reasons for adopting big data and analytics tools became more apparent in 2016, as well. An IDG survey discovered that the No.1 driver of investments in analytics is to improve customer relationships, at 55 percent, with making the business more data-focused coming in at a close second with 53 percent. It's clear that companies are finding uses for their information and are investing in the right tools to make it possible.
"The number-one driver of investments in analytics is to improve customer relationships."
Finance industry: Looking ahead in the new year
Businesses in every vertical are finding uses for big data, and the top trends for the new year will be a critical piece of the analytics puzzle for financial services organizations especially. According to ZDNet contributor George Anadiotis, there are a few reasons that banks adopt big data analytics tools: Namely, they're using them to improve and accelerate decision-making and to strengthen their compliance with industry regulations.
The fate of big data isn't just in the hands of data scientists and the actual technologies, however. As 2017 gets underway and more financial services organizations invest in big data and all its trappings, they will need to learn how to incorporate key findings into their operations – and that falls to the managers that best understand the business itself.
"[T]he true potential of data analytics lies to a large degree within the collective hands of managers and analysts, those who understand their business and know just enough about big data to add real business value," wrote Rick Brattin, an assistant professor of computer information systems at Missouri State University.
This means that banks that are turning to big data analytics tools need to know how to apply the insights gained from analysis of their own data. DealPoint from Brilliance Financial Technology helps banks collect and transform granular pricing data into business insights to drive increased profitability.
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