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- What is analytics?
- Predictive vs. prescriptive analytics
- What do you need to know to become an analytic professional?
- Looking at examples of good and bad metrics
- How mobile devices will shape analytics
Skill Level Appropriate for all
- Well for a long time companies have been using data to try and make better decisions. So analytics is simply a new buzzword to apply to that process. And the word analytics, I believe comes from a book Competing on Analytics written by Thomas Davenport around 2005, 2006. And that book popularized the name analytics simply using that for any situation which an organization is trying to use data to improve their decision making and do better with regards to their objectives. So let's give you a couple of examples of organizations that might use analytics.
So let's suppose you're in the education profession. You might be a K-12 teacher. You might be a college professor. You might be an administrator. So, what are some objectives you have? Well, one objective is to make the kids in K-12 more ready for college or the work force. And so basically, how can you use data to basically improve that? You might work for a company that's goal is to make money unlike the education business. So I think you'd probably would like to help your company make a higher profit. So, how can we use data help our company make a higher profit? You might work for a non-profit like the Gates Foundation.
The Gates Foundation's goal is fairly simple. Given the amount of money they spend, in most cases, save the most lives. So basically, can we use data to figure out what's the most efficient way per dollar spent to save lives. Obviously, there could be almost no more important objective than that. Well, another situation where you might want to use analytics. Is when you're trying to basically save for retirement. Which we all are doing, unless we're retired. And then we want to make our money last as long as possible. So the question would be, how should we allocate our assets so we have a minimum level or risk that gives us the desired expected return? We could put everything in a very risk investment but, if you'd bought NASDAQ at 5,000 in 1999, NASDAQ probably won't see 5,000 again for a bunch of years.
And so basically, you would have lost a lot of money. So using analytics in what we call Portfolio Optimization is a very important tool. Well all of us with our personal health, and then health care we know is basically costing the United States and other countries a lot of money. And the outcomes the United States achieves relative to other countries, is just not that good for the amount of money we spend. So, how can we use data to improve health care outcomes and also possibly reduce health care costs. So, those examples should give you some feel for where analytics are using data to solve, make better decisions will be helpful.