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

Optimizing query structure

A query is simply a request for information, so in the field of data analytics, a query is a request for data. It is how we call data from a database to our local environment. Several different programs allow you to query a database, and some are more popular than others, but often the biggest difference in the performance of queries is decided by how optimized they are. If you are making a simple query to a small database, efficiency and performance may not mean very much, but as the amount of data you are pulling gets bigger and your queries get more and more complicated, performance becomes a bigger issue. When you get to the point where a query takes hours or even days to run, you might want to consider optimizing it.

Filtering and subsets

First and foremost, it should be obvious that the less information you pull, the faster the process will be. Filtering is the process of being selective about which data you are querying. There are many ways to...