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CompTIA Data+: data exploration, analysis and visualisation
Your data needs to become usable business information. Structure exploration, analysis and visualisation to make results easier to understand. Strengthen your independence as an analyst and your ability to explain differences that inform decisions.
- Duration
- 5 days 40 hours
- Code
- C-DATA Code
- Certification
- CompTIA Data+ Certification
Accredited training for the CompTIA Data+ certification.
Presentation
Many organisations need to base business decisions on data. Data analysts are therefore essential, both for applying analysis and interpretation methods and for communicating relevant insights from that data.
This course develops valuable skills for analysing and interpreting data more effectively. Suitable for beginner data analysts, it teaches simple analysis methods and explains when and how to use more complex techniques. You will also learn to understand business requirements and present relevant data reports using appropriate visualisation tools. Finally, you will explore data governance principles, including quality and control.
By the end of this 5-day course, you will also be prepared for the CompTIA DA0-001 exam, included in our offer. Passing the exam is required to obtain CompTIA Data+ certification (see the Certification tab for details).
Objectives
By the end of this CompTIA Data+ course, you will be able to:
- Understand fundamental data model concepts and types, particularly data structures and file formats.
- Describe data acquisition methods and reasons for data filtering and profiling.
- Understand data manipulation techniques, languages and tools.
- Apply statistical analysis techniques appropriate to the context.
- Describe available analysis types and data analysis methods.
- Interpret business requirements to create an appropriate data visualisation in a report or dashboard with the required structural elements.
- Summarise key data governance concepts.
- Implement data quality control best practices.
- Take the CompTIA Data+ DA0-001 exam and earn certification.
Program
1. Data concepts and the common data environment (CDE)
- Identifying fundamental data model concepts.
- Understanding data schemas.
- Understanding data types and their characteristics.
- Comparing data structures, formats and markup languages.
2. Data extraction
- Explaining data integration and extraction techniques.
- Identifying common reasons for data filtering and profiling.
3. Data analysis
- Explaining commonly used data manipulation and optimisation techniques.
- Applying descriptive statistical analysis methods.
Explaining common analysis methods and their uses.
4. Data visualisation
- Explaining data visualisation concepts.
- Using visualisation types appropriate to the context.
5. Data governance, quality and control
- Expressing business requirements in report form.
- Designing report and dashboard elements.
- Identifying report templates.
- Explaining the importance of data governance.
- Applying data quality control.
- Explaining master data management concepts.
Audience
This course is intended for:
- Professionals responsible for developing and promoting data-driven business decision-making.
- IT professionals seeking CompTIA Data+ certification.
Prerequisites
To attend this CompTIA course, you should:
- Be able to read and understand English, Japanese or Thai for the DA0-001 exam.
- Have 18 to 24 months of experience as a data analyst or business analyst, familiarity with databases and analytical tools, basic statistics knowledge and data visualisation experience (recommended).
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Quiz / multiple-choice questions
- Practical exercises
Course highlights
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
