Every few months I devote a day to discover what are the current trends in analytics. I do this both to refresh the slides in my presentation and to refresh my mind to see what I may have missed.
The amount of literature out there on analytics continues to blossom at an amazing rate, making it a true challenge to stay well versed on what’s hot and what’s not. I read a new analytics themed book about once a month and I have well over 200 blogs, web sites and social media groups cataloged. So I like to think I’m pretty well versed on what is current.
Every time I go to list the top 5 analytics trends, I find that some things change and some stay the same. Ever since I have been doing this, data visualization is near the top. Business dashboards continue to be a big need. Business intelligence tools evolve and new ones’ pop up, but Tableau continues to be a market leader. 90% of us still use Excel for 90% of our analytics work.
Still a lot has changed. When I started this just 5 years ago no one was really talking about Big Data or Data Science. People just stared discussing using predictive analytics and now its all about prescriptive, even though most of us are still just doing descriptive analytics. For the newbie, descriptive = historical, predictive = forecast models, and prescriptive = really complicated models with a lot of variables to not just predict the future but to show a lot of alternatives as well.
Now if you talk to experts they make think nothing I have mentioned so far is new. But to the novice analyst or to the manager who really doesn’t care what’s it called, she just want’s results… its all new to them.
So I try each time to really find something really new not just to me but truly new to analytics. Six months ago that was the idea of using a data lake instead of a data warehouse. For those still unsure what a data warehouse is, it’s a collection of databases stored and/or connected centrally. Data lakes are used to describe the reality that more and more data is now unstructured data.
The discussion on what is unstructured data and how best to mine it and integrate it with structured data has really been at the forefront for a while now. Going from 80% structured to 90% unstructured in in just a few short years as mankind generates unprecedented amounts of data not easily captured in a database every day.
As of today, if I had to pick 5 topics to talk about it would be (1) Hiring Data Science and Analytics Talent, (2) Big Data Analytics, (3) Data Warehousing and Data Lakes, (4) Data Blending and (5) Mining Public Unstructured Data
Check back with me in a few weeks and this list will change.
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