Data _ Week 1_ discussion

Response 1:

Porcha wrote:

Good evening Professor and class,

· How is data analytics different from statistics?

Analytics is systematic data used for discovery, interpretation and communication in the vision of patterns. Statistics is when you organize, present or analyze that data.

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

Descriptive analytics is when the examination of the data is performed. Predictive analytics is analyzing the current facts and making predictions. Prescriptive analytics is the last phase of analyzing.

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

One way of doing this is sampling. For example: if you want to analyze the increase of quality care in the healthcare field you can sample patient complaints and ratings to analyze whether the quality care increased compared to a previous testing.

· 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?

Data analytics are used in order to determine customer satisfaction in my company. Surveys are text messaged to the patients and are analyzed by the big bosses.

Response 2:

KatV wrote

Statistics is collecting, organizing, analyzing, interpreting, and presenting data. Data analytics is the process of inspecting and cleansing that data then transforming it into a hypothesis that is molded.

Descriptive analytics describes what has happened in the business, predictive analytics is what could happen and prescriptive analytics is what should happen.

Businesses use data and statistics to be able to interpret what is happening within their business and progress to where they need to be.

In my organization and department we are always looking at raw data from how many patients we see, how many referrals we get, patient wait times, and staffing. We even use data to decide on customer satisfaction with vendors that we use. With COVID our operations were forced to practically shut down and only perform the most necessary cardiac testing and that was even limited to how many patient the entire building could bring in for the day. As more referrals have started to come in we have had to analyze what days we could increase operations and staffing since they are included in the occupancy rate in the building.