Publisher's Synopsis
Learn data analysis essentials and prepare for the Data+ exam with this CompTIA exam guide, complete with practice exams towards the end
Key Features
- Apply simple methods of data analysis and find out when and how to apply more complicated ones
- Take business requirements and produce a remote to the correct audience using appropriate visualizations
- Learn about data governance rules, including quality and control
Book Description
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 audiobook will be tested with the mock tests that appear in the final chapters. By the end of this audiobook, you'll be ready to pass the Data+ exam with confidence and take the next step in your career.What you will learn
- Become well versed in the five domains covered in the DAO-001 exam
- Gain an understanding of all the major concepts covered in the exam and when to apply them
- Understand the fundamental concepts behind ETL and ELT
- Explore various imputation and deletion methods to deal with missing data
- Identify and deal with outliers
- Learn about performing hypothesis testing
- Create insightful reports to showcase your findings
