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

Shaping data with common functions

In this section, we will talk about useful tools for shaping data that can be applied to almost any analytical program. There are lots of other tips and tricks that don’t fit nicely in any other section, but they are still important for you to know. Again, everything here, like the exam, is vendor-neutral. These are all concepts that can be executed in a wide range of data analytic tools and software.

Working with dates

Working as a data analyst, you will quickly learn that date variables are terrible. Every program handles them slightly differently and getting exactly what you want out of them is never easy. There are a few things that will help a little.

Know how to break up a date variable. This changes from program to program, but it is important to learn the basics of how to extract a day, month, or a year from a date variable. You can try to parse it using a simple delimiter, telling the program to break up this variable every...