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

Knowing important analytical tools

Okay, this one is brute-force memorization. You do not need to know how to use any particular data analytics tool or software for the exam, but CompTIA+ has come up with a list of names you need to know. There may be tools on the list that aren’t very popular, and there may be popular tools that aren’t mentioned on the list, but this is a list of the tools that will be in the exam. To be clear, this is all very high level—you just need to memorize the names and the vague purpose. The full list is as follows:

  • Structured Query Language (SQL)
  • Python
  • Microsoft Excel
  • R
  • RapidMiner
  • IBM Cognos
  • IBM Statistical Package for Social Sciences (SPSS) Modeler
  • IBM SPSS
  • Statistical Analysis System (SAS)
  • Tableau
  • Power BI
  • Qlik
  • MicroStrategy
  • BusinessObjects
  • Apex
  • Dataroma
  • Domo
  • Amazon Web Services (AWS) QuickSight
  • Stata
  • Minitab

This is quite a list, and you probably...