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


In this chapter, we learned about data wrangling and manipulation methods, or how to change your data into something you can use. We covered the different methods of merging data such as joins, blends, concatenation, and appending, and discussed the creation of new variables to help you, such as derived or reduced variables. Next, we discussed parsing data to break it down into little chunks. Then, we covered recoding variables, or changing current variables into a form you can use. Finally, we went over a list of common tools you can find in any analytical program that will help you in your work as a data analyst.

This wraps up Part 1, which was all about the preparation of data. Coming up in Part 2, we will start looking at analyzing data, and what you can do to learn more from it.

Pretty exciting, right? I’ll see you in the next chapter.