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)
1
Part 1: Preparing Data
7
Part 2: Analyzing Data
13
Part 3: Reporting Data
19
Part 4: Mock Exams

Data Wrangling and Manipulation

It is not an exaggeration to say that the majority of work done by the average data analyst revolves around preparing data for use. A large part of this is cleaning the data, as covered in the previous chapter, but it is more than just dealing with things that will cause errors or introduce bias. You will often have to get the data into a specific shape or format before you can use it. This step is often called data wrangling or manipulation. To be clear, when we use the word “manipulation,” we do not mean we are changing the outcome in any way; we are using it in the literal sense of handling and managing the data in a skillful way.

In this chapter, we will go over some of the most important skills in the data-wrangling process. We will talk about the different methods to combine datasets including different types of joins, blends, concatenation, and appending. Next, we will look at the addition of variables that add meaning, such...