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

Writing the right questions

Here, we will go over what makes a good question when it comes to hypothesis testing. This question is called many different things, depending on the field: business question, research question, or even just question. However, these are all the same thing. The question is the reason for the hypothesis testing! This question is what you are trying to answer.

Important note

The specifics of what makes a good question might change a little based on the field. For academia, you may want a question that will take several studies and a dissertation to answer, but for this book, we are focusing on the common role of data analysts working in the industry.

The parts of a good question

A good question has only two parts:

  • What two groups you want compared
  • The metric you want to use to compare those groups

Let’s think of an example. Does product X sell more per week than product Y?

We want to compare product X to product Y &...