With digital transformation efforts in full swing, all-new data sources coming online and the maturation of artificial intelligence, there’s plenty of learning and work to do that will certainly keep information technology leaders busy for the foreseeable future.
I believe 2018 will be remembered as the year where the wheat really separates from the chaff when it comes to data analytics. After a handful of years of building hype, we’re now starting to see real innovation when it comes to applying data to business decisions.
Having said that, there are three trends that I believe will especially dominate this year.
Thanks to all-new, cost-effective storage solutions (e.g., the cloud) today’s businesses are able to do things that they never thought would be possible. This has been amazing to watch as it has completely disrupted certain sectors. However, there’s a burgeoning issue. With easily attainable, cheap storage many organizations have started to hang onto their data assets, “Just in case.”
While the cost to simply host large swaths of data is not significant, there is a hidden cost associated with this. That’s because if and when you attempt to put the data to use, it will require a completely different architecture.
Unless IT leaders have really thought through their strategy, and have an established framework in place with use case-specific applications to action data assets, there is going to be some pain to endure. If you’re going to deploy a data lake, make sure to understand what it will take to action your data assets.
Blockchain Gets Applied in Other Industries
I think it’s safe to say last year is when blockchain had its coming out party. Between the rise of crypto currencies, speculative investors, and businesses and individuals alike simply trying to understand what it meant — exactly — blockchain dominated headlines in 2017.
After its mainstream debut, now I believe it’s time for blockchain to be embraced in other industries. For example, in recent months there have been discussions that it can be applied to the advertising industry to help clean up the digital media supply chain.
That makes sense, and it almost seems as if blockchain had been created for the advertising space. There’s just one problem: The throughput demands of real-time bidding (RTB) in a programmatic world presents a significant roadblock for the use of blockchain technology.
There’s a tremendous amount of opportunity for those who can figure out how to make blockchain work for RTB.
AI Continues to Mature and Becomes Real in the Mainstream
AI has been around for quite some time now, but it appears that after a lot of hype and worry people are finally starting to understand its true capabilities.
The conversation surrounding AI has shifted from that of man versus machine to a more realistic one: man and machine. Finally, the relationship is being understood as complementary.
As AI goes mainstream, the most dramatic example will be in the data analytics space. While data lakes and blockchain remains aspirational, tangible benefits are being recognized via the use of AI today. This leads me to forecast that we’re going to see widespread adoption in 2018.
As CTOs and CIOs are increasingly becoming more responsible for driving digital transformation, and implementing technologies — in partnership with various business lines — that maximize employee effectiveness and efficiency, AI-powered solutions are beginning to establish themselves as the standard for doing business at scale.
Rather than relying on the user to query the data and make connections, AI empowers users by providing on-the-ground assistance as needed so that they can deliver on their respective KPIs and drive bottom line results.
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