How is data analytics different from statistics?

I have seen in a lot of different settings were data and statistics were used as their counterparts or interchangeably. However, Data is more centered around individual increments of facts that is information that can be noted and/or used for analysis purposes; statistics are more in depth and consist of results from data analysis that have been completed.

Analytics tools fall into 3 categories: descriptive, predictive, and prescriptive. What are the main differences among these categories?

There are a few different types of data solutions that analytical tools fall under, and they are Descriptive which is when data is looked at statistically and tell users what has happened in the past, vital to helping an organization by giving context to help stakeholders interpret information; predictive focuses on historical data and process it into machine learning that takes into account key patterns and trends; prescriptive is an enhancement of predictive because now that you know what may happen in the future, it can suggest a numerous course of action and outlines with possible implications.

Explain how businesses use analytics to convert raw operational data into actionable information. Provide at least 1 example.

A great example of using raw operational data and converting it into actionable information is the scrum framework. One the product owner (PO) acts as a middleman between the client and the development team. The PO gathers information from the client (raw data) then goes back to the Scrum Master (SM) and the Develop Team (DevTeam) to give them the product backlog of user stories of items that need to be completed to convert the raw data into deliverables to get to a potential releasable product in increments called sprints.

 Consider the organization you work for (or another organization you’re familiar with). Does this organization use data analytics? If so, how is it used? If not, how could the organization use data analytics to improve its performance?

Yes, I work for Wells Fargo in their foreclosure department currently and we do use analytics to manage workload and met deliverables. I would say that we use a lot of prescriptive data because after tons of analysis we know what the future holds so from there we come up with many solutions to make sure that workload has KPIs, SLAs, escalations options, downtime factored in and much more to make sure that we can have productive days while doing our day-to-day operations.