Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying CompTIA Data+: DAO-001 Certification Guide
  • Table Of Contents Toc
CompTIA Data+: DAO-001 Certification Guide

CompTIA Data+: DAO-001 Certification Guide

By : Cameron Dodd
5 (11)
close
close
CompTIA Data+: DAO-001 Certification Guide

CompTIA Data+: DAO-001 Certification Guide

5 (11)
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)
close
close
1
Part 1: Preparing Data
7
Part 2: Analyzing Data
13
Part 3: Reporting Data
19
Part 4: Mock Exams

Parsing your data

In this section, we will talk about what parsing is and some common ways it is used. Sometimes you will receive data in a format that is not readily usable. Whether you are pulling data from a website, working with JSON files, or have big chunks of text, you will need to parse your data. There are many different parsers that you can use, depending on what you need to parse, but the general idea is that you are breaking a single large piece of data into several smaller pieces of data that can be easily identified and processed.

Natural Language Processing (NLP) is a field of data analytics that specializes in analyzing, you guessed it, language. Spoken or written, NLP is trying to translate common speech into actionable data. Parsing is necessary for even basic NLP.

Important note

In reference to NLP, parsing is called tokenization because it is breaking up the text into words, and each becomes its own object or token.

Let’s consider an example...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
CompTIA Data+: DAO-001 Certification Guide
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon