7 years ago, my peers and I used the terms “data” and “analytics” in CIO meetings. We didn’t use the phrase “cognitive analytics.” Today, all the cool-kids are using the phrase.
Why should you care about Cognitive Analytics?
Enterprises have loads of data and will continue to amass it, have challenges leveraging it, analyzing it, getting info to make best (and quick) decisions for the business, etc. They need to figure it out fast — this is a timely matter! …and…sure…
- All along we’ve known that data is important — no enterprise can escape it because all companies are all about analytics of data (yup, you can believe me and Forrester)! How else do we know what’s going on? Water-cooler discussions?
- All along we’ve known that analytics are important — without them we can’t get insight from our data. How else can we make smart business decisions? Intuition?
But what about having technology that can basically take the lead on why, what, how, and when to data mine, analyze, and provide you with elevated insight to make optimal business decisions and help you be an expert?
Imagine this: you have a machine learning agent (with AI, of course) that can crawl through all available data, sort, learn, and conceptualize for you! This agent is your personal expert — there to help you look, feel, and sound smarter! This expert helps you make the best decisions — helping you and your enterprise succeed.
Boom! there’s your answer: you should care about Cognitive Analytics because this technology can and will help address your data challenges and save the day with phenomenal insights (plus, Cognitive Computing won’t ever take credit for your work — he will be your sidekick and you will be the heroine)!
Let’s take it up a notch and take it from words to video (and money). Watch this really cool video on cognitive analytics from the IBM Lab.
That’s neat right? You can make the right acquisitions and increase the profit of your company. Money.
I’m Listening. So, how does it work and what is the key benefit of Cognitive Analytics (versus regular Data Analytics)?
Great question! I like how Tom Davenport, Director of Research at the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics, elaborates on just your question, here:
“The key benefit of cognitive technologies is that they can solve some problems that traditional analytics can’t. In the world of big data, for example, the data from sensors, social media, and online applications often flow and accumulate much faster than humans could possibly analyze or act on it. Without machine learning to create the models for such data, it couldn’t be analyzed at all.”
I agree with Davenport and to that I add: cognitive analytics is cool but it’s not going to have a timely and purpose preset. You’ve got to know where your enterprise is, when to use the technology and what you’re going to use it for. Otherwise, you may end up spending a ton of money without really getting the most bang for your buck.
I hear you. I want to mull it over. What should my enterprise consider before jumping on the cognitive analytics wagon? What are use-cases and what are potential results I can expect for my enterprise?
Wow. Lots of questions. Good. I’ll try to keep answers simple and useful.
- Before jumping into the cognitive analytics wagon, focus on the fact that only you know your company best. What’s your data situation? What about your analytics situation? Can Cognitive Analytics solutions be deployed at this point? Could Watson Analytics and DataWorks help your enterprise? Here’s an article to get you going on your best next step.
- CIO.com put together a great list of use cases here.
- Cognitive analytics allows you to: save costs and optimize your business; identify new business opportunities; analyze injury reports to improve safety; benefits abound; and more.
Cognitive Analytics is so cool! I want to learn more.
Yes! Right? Imagine the possibilities with Cognitive Analytics! I’ll leave you with Cognitive Analytics predictions straight from the IBM Big Data and Analytics Hub.
It is predicted that Cognitive Analytics will:
- become inescapable in everyday life
- become the chief focus of innovation
- begin to converge all big data
- become the hottest speciality in data science
- take root in global governance
- become the principal personalization tool
- start to automate most data analytics
- drive further scaling in cloud data services
If you want to read more about anything in particular, leave in the comments section.
Originally published at www.huffingtonpost.com on September 23, 2016.