Data is only valuable when it drives action. This course helps participants turn raw data into insights using practical analytics techniques. Participants will learn to identify business requirements, mine datasets, perform statistical analysis, and present findings effectively.
Learning Outcomes:
- Apply data mining, forecasting, and modelling techniques to reveal trends and patterns in a given dataset
- Apply data transformation techniques and principles to structure datasets into meaningful insights that drive business decisions
- Execute database queries to retrieve unique information from two tables or datasets
- Generate performance dashboards to reveal business insights from data studies
Key Topics:
- Data lifecycle and analytics frameworks
- Data quality, mining, and governance
- Analytical methods and tools
- Certification preparation for CompTIA Data+ (DA0-001)
Exam Details
This course is designed to build participants’ understanding of key concepts and domains covered in the CompTIA Data+ certification.
The CompTIA Data+ certification validates the skills required to support data-driven business decision-making, including data mining, data manipulation, visualisation, basic statistical techniques, and maintaining data quality across the data lifecycle.
The certification is suitable for early-career data analytics professionals and demonstrates the ability to support and communicate business intelligence through effective data handling and presentation.
To maximise success, participants are strongly encouraged to complement the course with additional self-study, revision of course materials, and dedicated practice before attempting the exam.
Data Concepts and Environments
- Identifying basic concepts of data schemas
- Understanding different data systems
- Understanding types and characteristics of data
- Comparing and contrasting different data structures, formats, and markup languages
Data Mining
- Data integration and collection methods
- Identifying common reasons for cleansing and profiling data
- Executing different data manipulation techniques
- Common techniques for data manipulation and optimization
- Applying quality control to data
Data Analysis
- Applying descriptive statistical methods
- Describing key analysis techniques
- Understanding the use of different statistical methods
Visualisation
- Using the appropriate type of visualisation
- Expressing business requirements in a report format
- Designing components for reports and dashboards
- Distinguishing different report types
Data Governance, Quality, and Controls
- Summarising the importance of data governance
- Master data management concepts
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