From the course: Introduction to Business Analytics (2020)

Three types of analytics

From the course: Introduction to Business Analytics (2020)

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Three types of analytics

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- [Instructor] What comes to mind when you hear the term analytics? Is it big data? Predictive modeling? Statistics? These are all common answers that I often hear, and these terms are all related to analytics, but people tend to focus on the flashier aspects that fall under the umbrella-term of analytics. The truth is that 90% of businesses today are not on the advanced level of analytics that require big data and predictive modeling. They are only on step one of three, in terms of phases of analytics. The first type of analytics is called descriptive analytics. And this type of analytics is by far the most common. It looks back at your historical trends to shed some light on what's working. It mostly leverages internal data sources that your organization is creating, such as sales or marketing data. Now the second type of analytics is called predictive analytics. This phase is quite a bit more sophisticated than descriptive, as it leans on more advanced forms of calculations to get the job done. An example of this is a linear regression model. This phase actually builds off of descriptive analytics in that you need solid data sources to really get a rich enough data set to build a predictive model. And finally, the last phase of analytics is called prescriptive analytics. This form takes predictive modeling a step further by not only providing a predictive model, but also giving recommendations on how to capitalize on these potential future occurrences. This process is often referred to as creating an optimization model. Now let me show you prescriptive analytics in action. The healthcare space is a great setting for prescriptive analytics, because there are huge amounts of data and the stakes couldn't be higher. They're literally life or death. Healthcare systems are now using prescriptive analytics to reduce readmission rates by studying all the factors that contribute to a patient being readmitted, and proactively addressing these issues. A specific example is Aurora Health Care, who saved six million annually by using prescriptive analytics to reduce their readmission rates by 10%. In this course, we will focus mainly on descriptive analytics, this will give you a sound foundation moving forward as your business grows, and you will be able to successfully tackle the first phase of implementing analytics for your organization.

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