What is Data Analytics? - Definition & Tools

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  • 0:03 Introduction to Data Analytics
  • 1:25 Tools Used for Data Analytics
  • 4:20 Lesson Summary
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Lesson Transcript
Instructor: Brianna Whiting

Brianna has a masters of education in educational leadership, a DBA business management, and a BS in animal science.

In this lesson, we'll learn about data analytics. We'll define it and learn about some of the many tools used for data analytics. The lesson is followed by a quiz.

An Introduction to Data Analytics (DA)

Let's imagine that you own your own business. Your business is responsible for designing new products in the field of education. Currently you employ over 100 individuals that actively design new educational products for schools and parents to use.

After five years of being in business, you realize that your current method of exploring and examining data, is slow and very time consuming. If you could find another way to analyze all of the educational data your employees compile, your company could be more efficient with creating new and exciting educational materials. You decide to take a course about data analytics to learn a better way to handle the data your company acquires.

Data analytics, also known as DA, is the method of examining and analyzing raw data so that conclusions can be drawn. Data analytics is a valuable part of science centered industries in verifying or disproving current theories or models. The purpose of DA is to sort through data in order to arrive at a conclusion.

For example, let's say your company sells toy clocks to help children learn how to tell time. If you wanted to know who is buying this learning material, you might create a table to help you visualize the clientele. You can break up the data into location, age, type of school system, etc. using the tool.

Tools Used for Data Analytics

Because we know that data analytics is the method of analyzing data to come to a conclusion, it is important to have resources and tools that help find that data and organize it. Let's explore some of the useful DA tools that companies can use to gather, group, and visualize their data.

One tool is Google fusion tables. This is an application that allows you to actually visualize data. With google fusion tables, a company can gather all of their data, visualize it, and share it through the application. Here's an example of a table that can be made using Google fusion tables.

Google Fusion sample table

Another tool is OpenRefine. This software is basically a housecleaner, meaning OpenRefine groups similar entries together so that spelling, spaces, etc. can be checked and made ready for analysis.

For example, let's say that your current data about the toy clocks are contained in three different formats. Because three different people entered the data, they all have different styles. One person capitalized every word, while another person added extra spaces between the first and last name of each buyer. Using OpenRefine can help make sure that all of the formatting is the same so that the data can be grouped together nicely.

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