Book Image

CompTIA Data+: DAO-001 Certification Guide

By : Cameron Dodd
Book Image

CompTIA Data+: DAO-001 Certification Guide

By: Cameron Dodd

Overview of this book

The CompTIA Data+ certification exam not only helps validate a skill set required to enter one of the fastest-growing fields in the world, but also is starting to standardize the language and concepts within the field. However, there’s a lot of conflicting information and a lack of existing resources about the topics covered in this exam, and even professionals working in data analytics may need a study guide to help them pass on their first attempt. The CompTIA Data + (DAO-001) Certification Guide will give you a solid understanding of how to prepare, analyze, and report data for better insights. You’ll get an introduction to Data+ certification exam format to begin with, and then quickly dive into preparing data. You'll learn about collecting, cleaning, and processing data along with data wrangling and manipulation. As you progress, you’ll cover data analysis topics such as types of analysis, common techniques, hypothesis techniques, and statistical analysis, before tackling data reporting, common visualizations, and data governance. All the knowledge you've gained throughout the book will be tested with the mock tests that appear in the final chapters. By the end of this book, you’ll be ready to pass the Data+ exam with confidence and take the next step in your career.
Table of Contents (24 chapters)
Part 1: Preparing Data
Part 2: Analyzing Data
Part 3: Reporting Data
Part 4: Mock Exams

Calculating derived and reduced variables

In this section, we will talk about specialized variables that you can create that will help you as a data analyst. You will find that raw data, even clean raw data, can be difficult to interpret. When looking at a functional dataset that is actively being used by a data analyst, you will almost always find variables that were not present when the data was originally recorded. Instead, these variables were added later and contain some logic that allows them to create a new value based on those that were recorded.

Derived variables

Variables that use logic that relies on other variables are broadly called derived variables, though some also refer to them as calculated variables or fields. The idea is just that this variable was not observed but was generated based on data that was observed. If this definition seems a little vague, that’s because it is. There are as many derived variables as there are stars in the sky and they come...