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

Exploring your data

EDA is a general term for a broad category of analyses that are used to understand your data better. Is that definition a little vague? Yes, but the term means slightly different things to different people. Even what analyses fall into this category are up for debate. What is EDA, then? It’s dipping your toe into the water to check the temperature before jumping into the data lake.

Important note

It should be noted that some analysts include the cleaning and wrangling processes in what they consider EDA because they are all things you do to prepare your data for use. However, for the purpose of this exam, they are considered separate.

When you first receive a new dataset, before you know what questions to ask or analyses to run, you need to understand some basic information about the data. This can take the form of basic descriptive statistics, simple charts or visualizations, or even simple modeling or machine learning algorithms. What analyses...