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Author's profile photo Timo ELLIOTT

Analytics: What Happened in 2017 and Where Is 2018 Going

Every year, the nice folks at reach out to various experts to get their opinions on the greatest trends in analytics. You can get the full list of answers here, but here are my answers to their questions.

What was, in your opinion, the most important thing that happened in analytics in 2017?

The biggest change was a massive wave of publicity about the power of data, with many algorithmic breakthroughs. Computers are now better at transcribing speech, reading lips, and tagging images than people. AlphaGo Zero bested 2,000 years of human learning about the strategy of Go in just three days, with no prior knowledge of the game!

The result was that use of data to change how society works was discussed at levels never before seen. Data and analytics has been the hottest thing in the IT industry for decades, and in business for several years—but now it’s the hottest thing in society as a whole!

What is, in your opinion, the most important thing that will happen in analytics in 2018?

First, analytics will be at least four times more important for the business than it has been in the past. New technology means we’ll be able to deliver much more, with the rapid implementation of AI to create “self-improving processes”—everything from predictive maintenance to lights-out finance—and to augment traditional analytics, with natural-language interfaces, automatic sense-making, more intelligent data matching, and much more.

There was a lot of talk about robotization in 2017—how do you think this will affect businesses in 2018?

There will be a huge amount of automation using machine learning in 2018. But it will be mostly about saving every one of us a few hours of work a week, rather than eliminating jobs—it will displace work rather than replace workers. The result is that we will be able to spend less time chasing information, and more time thinking about the big strategic changes required by digital transformation.

“Big Data” is said to be a dying term, and “Business Intelligence” appears to go the same direction. Do you agree with this, and if so, what do you think is the best term that can replace these?

Ironically, this isn’t backed up by the available data, at least according to Google Trends—in fact, all terms associated with any aspect of analytics are on the rise. Personally, I hate semantic or nomenclature wars. They’re a complete waste of time for everybody except the analysts and bloggers that get traffic from writing polemic articles about how somebody else is using a term incorrectly.

Instead of arguing over words, everybody should concentrate on making sure that there are no misunderstandings on a particular project, that everybody agrees on what information is to be made available, and why, and how.

What new concepts and buzzwords do you think will appear in analytics in 2018?

  • Data governance. All forms of data governance will be huge, especially with the European Union General Data Protection Regulation (GDPR) going into force shortly. Data sovereignty will be paramount—who “owns” data, who decides how it is shared, and to whom. Data trust will be a huge issue—companies will have to give customers more control over their identity information and data.
  • Data warehousing. Big Data warehousing will become mainstream, seamlessly combining data lakes and enterprise data warehouses into a single architecture using data catalogues, data orchestration, and data pipelines.
  • HTAP and Translytic architectures. Operations and analytics will come together. It’s been a long time coming, but “HTAP” (hybrid transactional analytical processing) or “Translytic” architectures are poised for huge growth, powered by a new generation of in-memory ERP systems that enable real-time analytics and decision-making as part of business transactions.
  • Hybrid analytics. Cloud analytics is fast becoming mainstream, but many organizations aren’t ready to give up their traditional on-premise approach. The answer is to do both, as seamlessly as possible — for example, by enabling analytics from the cloud without having to move data off-premise.
  • Purposeful data. Data is my favorite superpower—“Ask not what data can do for you, ask what it can do for the world!”
  • Augmented intelligence. 2018 will see the next steps in AI — using it for enterprise uses, such as powerful image recognition, that up until now just weren’t possible.
  • LoT or “location of things” analytics.
  • X-Reality analytics. From viewing information to visualizing it, X-Reality is an umbrella term for the relationship between data and augmented reality/virtual reality/mixed reality, and so on.

This blog originally appeared on Timo Elliott’s blog, Digital Business & Business Analytics. Connect with him here, on his blog, or on Twitter at @TimoElliott

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