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

What this book covers

Chapter 1, Introduction to CompTIA Data+, covers what topics the CompTIA Data+ certification exam will include, as well as how the exam will be administered.

Chapter 2, Data Structures, Types, and Formats, discusses how data is stored, covering high-level concepts of database structures down to specific file types that you will need to know about.

Chapter 3, Collecting Data, covers all the methods that are available for you to use for collecting data.

Chapter 4, Cleaning and Processing Data, covers various types of data, and how to clean and process them for use.

Chapter 5, Data Wrangling and Manipulation, teaches you how to shape the data into a form that various applications can use.

Chapter 6, Types of Analytics, covers the most common types of analyses, and various examples of each of them. You will learn to perform EDA, performance analysis, trend analysis, and various methods for each.

Chapter 7, Measures of Central Tendency and Dispersion, introduces you to measures of central tendency and measures of dispersion, as well as how to calculate them. You will learn what a probability distribution is, and understand dispersion, means, medians, and various other measures.

Chapter 8, Common Techniques in Descriptive Statistics, covers specific analytical techniques that are commonly used in data analytics and how to use them to calculate various statistics.

Chapter 9, Hypothesis Testing, looks at the fundamental concepts you need to understand about hypothesis testing and why it is important. You will learn about null and alternative hypotheses, the p-value, and other concepts.

Chapter 10, Introduction to Inferential Analysis, covers various types of statistical analyses, which will help you understand data better.

Chapter 11, Types of Reports, covers various types of reports, and how you can use each of them for various types of data analysis.

Chapter 12, Reporting Process, covers how you can create a report based on a question, or the structure and format that you need to follow for it.

Chapter 13, Common Visualizations, covers the most common visualizations that you can use to showcase your data, including heatmaps, treemaps, bubble charts, and many more.

Chapter 14, Data Governance, covers how you can manage your data and keep it secure. You will learn about various security measures and requirements, and you will understand what a data breach is and how to react to it.

Chapter 15, Data Quality and Management, covers various data control and quality checks, which will ensure that your data reports are accurate and useful.

Chapter 16 and Chapter 17, Practice Exams One and Two, will put you through a couple of practice exams that are designed around the Data+ exam so that you can prepare yourself for it. They have answers to every question, along with the context and explanation for each of them.