Things to be Thankful for this Thanksgiving

Andy McCartney's picture
 By | november 22, 2016
november 22, 2016

Another Progressive Year in Our Industry

I must say it has been a fascinating and dynamic year in the BI and analytics industry. As someone who's managed data and built dashboards since the early 90s, I've come to realize that in some ways, nothing has changed, but in other ways, so much has progressed. It amazes me how we still exist in such a fast-paced, ever-changing business environment.

We could be lawyers or accountants, where practices and strategies are relatively stagnant, but we are not so let's celebrate a few aspects of analytics that have either emerged or accelerated this year:

  1. Data Driven Everything. We truly live in a data-driven world, where more people are analyzing data at home, at work, and when traveling. Look around and consider just how much of your life is 'data-driven', whether pulling up a real-time app of traffic or train departures, monitoring your step counts or sleeping patterns, or receiving alerts on your bank spending or stock trades. Organizations are now trying to get high-value data into the hands of all their business stakeholders, and on users' terms so that smarter business is actually possible for everyone. 'Adoption' is the key word here, and there is no longer any reason why all your employees, partners, and customers cannot attain considerable value from your wealth of corporate and related data sources. One of Information Builders' sweet spots is the enablement of broad adoption: check out this short video.
  2. Automation. Automation is appearing in many aspects of life, including vehicles, smart homes, retail services, and healthcare. The benefit may be convenience, cost savings, and risk management, and consumers can easily configure and enable that automation. In our industry, automation has been around for a while in the form of scheduled and burst reports, charts, and alerts based on time or value triggers. Now we are getting more expansive with automation, to the point that machine learning can not only execute a prescriptive recommendation to a user, but also automate the decision based on real-time data. Automated analytics can also be invisibly embedded within another application, combining data from the host and analytics app to determine and then execute the best next step. FYI here is an analyst report on embedded BI.
  3. Natural Language. In order to expand the reach and applicability of BI and analytics to users of wide and varied proficiency levels, new interfaces and options are appearing. Many are calling this ’Smart BI'.  One of these options is Natural Language Generation (NLG). NLG is a subfield of artificial intelligence, which produces language as output on the basis of data input. It is not a new concept – what is new, however, is the increase in adoption of NLG into the enterprise. NLG software immediately adds value to data by identifying patterns and outliers, and conveying it through professional, conversational language. The result? Intelligent narratives that efficiently communicate the insights buried in data that people can comprehend, act on, and trust. NLG software generates news stories, industry reports, headlines, and analytical narratives – at scale and without human authoring or editing. The outcome is an alternative deployment option that increases value and accessibility to analytics. Here is a web page introducing NLG.
  4. The Election and Interest in Predictive. . Has there ever been a more apparent flaw in predictive modeling and polling forecasts than in the election we just witnessed? A variety of prediction sources claimed Hillary Clinton was between 71 percent (FiveThirtyEight), 85 percent (NYT) and 95-99 percent (Princeton) likely to win.  Well for a variety of reasons (assumptions, sample sizes, systematic errors) it didn’t shake out that way at all, indicating there’s a long way to go before we have a reliable, robust way to predict election outcomes based on polling. Perhaps this election has raised the awareness of predictive analytics, and opened the door to more conversations and opportunity for predictive business, albeit with greater transparency and deliberation in the modeling. We have been deploying predictive for many years – see RStat here.

That's it for this Thanksgiving. All of us at Information Builders wish you a wonderful family season and we look forward to another remarkable and progressive year of BI and analytics.

Andy McCartney