CompTIA Data+ Study Guide: Exam DA0-001
Get ahead with our CompTIA Data+ Study Guide: Exam DA0-001 online course, and gain the skills you need to excel in data analytics and career advancement.
(DA0-001.AE1) / ISBN : 978-1-64459-349-3About This Course
This CompTIA Data+ Study Guide: Exam DA0-001 online course will help you develop essential data analytics skills for presenting information to stakeholders & decision-makers. Through engaging lessons and practical tests, you will learn how to collect, analyze, and interpret data effectively. Our course covers all exam objectives, ensuring you are well-prepared to pass the CompTIA Data+ certification exam and advance your career in data analysis.
Skills You’ll Get
- Proficiency in collecting, analyzing, and interpreting various types of data.
- Understanding and applying data governance and quality management principles.
- Mastery of statistical analysis techniques, including descriptive and inferential statistics.
- Competence in using data analytics tools such as spreadsheets, programming languages, and machine learning software.
- Ability to design and develop effective data visualizations, reports, and dashboards.
- Knowledge of database management and data acquisition methods.
Get the support you need. Enroll in our Instructor-Led Course.
Interactive Lessons
9+ Interactive Lessons | 307+ Exercises | 150+ Quizzes | 191+ Flashcards | 91+ Glossary of terms
Gamified TestPrep
50+ Pre Assessment Questions | 2+ Full Length Tests | 90+ Post Assessment Questions | 180+ Practice Test Questions
Hands-On Labs
25+ LiveLab | 8+ Video tutorials | 10+ Minutes
Introduction
- The Data+ Exam
- What Does This Course Cover?
- Exam DA0-001 Exam Objectives
- DA0-001 Certification Exam Objective Map
Today's Data Analyst
- Welcome to the World of Analytics
- Careers in Analytics
- The Analytics Process
- Analytics Techniques
- Data Governance
- Analytics Tools
- Summary
Understanding Data
- Exploring Data Types
- Common Data Structures
- Common File Formats
- Summary
- Exam Essentials
Databases and Data Acquisition
- Exploring Databases
- Database Use Cases
- Data Acquisition Concepts
- Working with Data
- Summary
- Exam Essentials
Data Quality
- Data Quality Challenges
- Data Manipulation Techniques
- Managing Data Quality
- Summary
- Exam Essentials
Data Analysis and Statistics
- Fundamentals of Statistics
- Descriptive Statistics
- Inferential Statistics
- Analysis Techniques
- Summary
- Exam Essentials
Data Analytics Tools
- Spreadsheets
- Programming Languages
- Statistics Packages
- Machine Learning
- Analytics Suites
- Summary
- Exam Essentials
Data Visualization with Reports and Dashboards
- Understanding Business Requirements
- Understanding Report Design Elements
- Understanding Dashboard Development Methods
- Exploring Visualization Types
- Comparing Report Types
- Summary
- Exam Essentials
Data Governance
- Data Governance Concepts
- Understanding Master Data Management
- Summary
- Exam Essentials
Today's Data Analyst
- Understanding Data Analytics Techniques
Understanding Data
- Understanding Data Types
- Identifying Categories of Data
- Understanding Common Data Structures
Databases and Data Acquisition
- Creating a Data Model through ERD
- Normalizing Data from 2NF to 3NF
- Normalizing Data from 1NF to 2NF
- Normalizing Unnormalized Data to 1NF
- Sorting Data
- Removing Unnecessary Data
- Updating Existing Data
- Retrieving Specific Data
Data Quality
- Eliminating Redundant Data
- Concatenating Data
- Understanding Data Quality
Data Analysis and Statistics
- Performing Data Analysis
- Understanding Descriptive Statistics
Data Analytics Tools
- Saving Data in Excel
- Representing Data
- Analyzing Data Using Python
- Identifying SQL Commands in Data Analytics
Data Visualization with Reports and Dashboards
- Visualizing Data Using a Line Chart
- Visualizing Data Using a Histogram
- Visualizing Data Using a Bar Chart
Data Governance
- Understanding Laws in Data Governance
Any questions?Check out the FAQs
Still have unanswered questions and need to get in touch?
Contact Us NowThe CompTIA Data+ exam consists of a maximum of 90 questions.
The CompTIA Data+ certification has no formal prerequisites. However, it is recommended that candidates have experience of 18-24 months in a report/business analyst job role.
The CompTIA Data+ certification holds weight for 3 years following your successful exam attempt.
The time it takes to study for the CompTIA Data+ exam varies depending on your background and experience, but most people spend around 2 to 3 months preparing for the exam with consistent study.
The CompTIA Data+ exam costs 253 USD.
Yes, the CompTIA Data+ certification is worth it for individuals looking to validate their data analytics skills and enhance their career opportunities in the growing field of data analysis.
The CompTIA Data+ certification can benefit your career by validating your data analytics skills, increasing your job prospects, and potentially leading to higher-paying positions in data analysis and related fields.
The exam consists of multiple-choice questions, drag-and-drop activities, and performance-based questions.
The salary for individuals with CompTIA Data+ certification can vary based on factors such as location, experience, and job role. On average, professionals with data analytics skills and certifications like CompTIA Data+ can expect to earn between $60,000 and $80,000 annually. In higher-demand areas or more advanced positions, salaries can exceed $100,000.