photo credit: Jon Ottosson via Unsplash

An earlier version of this post originally appeared on bicorner.com.

Early January is the time of reflection and prediction. Here are my comments on the key BI and Big Data trends that I saw developing in 2015 and that will continue to play out in 2016.

A broader awareness of and engagement with data – This trend is driven by the smartphone and consumer devices such as the Fit Bit that literally put meaningful data in people’s hands.  There is a growing expectation to be able to access data and to do so in a way that is convenient and visually appealing.

Big data becomes data – There was more data generated in the last two seconds than the previous two millennia. Pick your favorite made-up statistic. In 2016 everyone will be used to the idea that there is a lot of data being captured now and it is only going to increase.

Excel remains a popular analytics tool – BI vendors continue to wage war against spreadmarts and there are definitely some shortcomings with spreadsheets. However, for 2016, and probably much longer, Excel is here to stay as an all-purpose and flexible BI, analytics and data science tool.

From mobile-first to mobile-primary – If your reports, data visualizations and advanced analytics are not available to business users on their smartphones than they might as well not exist. In 2015, the desktop (or laptop) ceased to be the primary client web browser. Users expect to have a similar user experience across devices and to be able to go from one platform (phone – tablet – laptop) to another seamlessly.

The big legacy software vendors are losing influence – The open source movement has disrupted the big vendors by enabling smaller software companies to assemble targeted solutions quickly using open source frameworks. CIOs are now more likely to be managing a portfolio of vendors and products of varying sizes rather than a handful of big vendors with which they spend most of their budget. As this trend continues, there will be more spitting up (like HP and Citrix) and combining (such as Dell and VMWare; IBM made 11 acquisitions in 2015). As software license revenues decline in 2016, the big vendors will focus more on selling cloud products and professional services where they can leverage their access to capital (to build out cloud infrastructure) and long standing customer relationships (to sell premium consulting services).

The BI/DW Cloud – The security and bandwidth arguments against cloud based data warehouses and analytics are no longer very convincing. Microsoft Azure and Amazon Redshift are the leading cloud products to watch and it will be interesting to see competing products emerge from Google, IBM and elsewhere.

IBM Cognos Analytics 11 hits the market – I am looking forward to helping Cognos customers leverage their investment in Cognos technology and keep up with the above trends. From what I have seen so far, the focus of the new release is self-service BI and data discovery, on trend with what large enterprise customers are looking for in BI software. I think the success of IBM with the new version of Cognos BI will hinge on the mobile user experience and its capacity for handling huge volumes of data.

My non-trend for 2016 is data governance  – Data governance is getting more attention as the evidence grows that loosely governed self-service BI solutions promote analytics sprawl and data confusion. Gartner estimates that less than 10 percent of self-service BI initiatives will be governed sufficiently to prevent poor business decisions caused by data problems. This is nothing new, as data quality has been a concern since BI software first became mainstream. The problem with data governance is that the benefits are too long term for most organizations to justify the investment.

This is why data governance is my 2016 non-trend. With greater volumes of data to work with, in many cases the standard for data quality can be much lower. Another factor is the accelerating pace of change: why spend time and money worrying about data that will be of questionable value in a year’s time? In any case, preventing unknown future problems rather than solving immediate data issues is a luxury few companies will want to buy.

So these are my seven trends to watch and one non-trend: I am looking forward to seeing how these play out in 2016.