If you're new to the world of business analytics, we'll you're not alone.  With data driven decisions, business analytics and data analytics, have converged to some extent.  There are specific roles like analysts and data scientists, but hybrid roles are becoming the norm. 

Here's an example of how each can be applied in a Customer Support business function.
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There are 4 types of analytics. The two "D's - Descriptive and Diagnostic", are more backward looking, while the two "P's - Predictive and Prescriptive are forward looking".
Define one analytics question corresponding to each of the four styles of analytics: descriptive, diagnostic, predictive, and prescriptive. (Please list your four questions using bullet points and specify which style of data analytics each question pertains to.)
·       Descriptive: How can historical data be used to glean insights about type of customers who connect with the firm?
·       Diagnostic: How can customer feedback and business representative data be combined to create relationships between time of call-in, issue resolution and time to resolution?
·       Predictive: How to take external data factors such as education, sex, salary, geographical…etc, and create models that can provide insights into product quality and logistical bottle necks?
·       Prescriptive: How to feed self-learning algorithms, that can ingest multiple data variables and suggest product and service improvements?
Which of these questions you conceived do you think is the most important to answer, and why? Why is this question more important than the other three questions? How would answering it help drive business value?
I believe that Prescriptive analytics is the most important, as it can leverage excerpts of relevant data from the other three styles of analytics and suggest insights/recommendations for future improvements.
Time to Insights about consumer behavior has become a key differentiator for a firm, as the consumer pallets are constantly changing.  Prescriptive analytics can take data from sales, operations, marketing…etc and create a persona based approach.  These personas can allow for interactions where consumers feel a personalized approach.  The personas can be constantly updated through continuous analytics, thereby ensuring consistency and alignment with consumer expectations.
As a connected consumer, the power has shifted from producers to consumers.  The Prosumers, through their direct and indirect channels can impact the business and its brand.  Controlling the narrative therefore has become extremely integral in the age of consumer influencers.  By leveraging a persona-based approach, which predictive analytics can help create and constantly update, businesses can control and influence the narrative.  Consumers can therefore become brand ambassadors, driving value and growth for the business. 
Feel Free to apply this as a model to any business function.