Certified Business Data Analyst (CBDA) Exam Preparation Programme
1Summary
Organisations today are sitting on more data than ever, but volume alone doesn't translate into better decisions — only structured, accurate analysis does. That gap is exactly what a certified business data analyst is trained to close.
This programme, delivered by the Arab British Fellowship Training Academy, prepares participants for the Certified Business Data Analyst (CBDA) credential while building the practical tools needed to turn raw data into insight that improves organisational performance. It suits professionals at any career stage who want to strengthen how they collect, analyse, and communicate data-driven findings.
2Objectives and target group
Who Should Attend?
- Business analysts looking to sharpen their data analysis skills.
- Project and operations managers who rely on data analytics for decision-making.
- IT and database professionals expanding into business analytics.
- Professionals pursuing the CBDA credential to advance their careers.
Knowledge and Benefits:
By the end of the programme, participants will be able to:
- Explain how a business data analyst supports and improves decision-making.
- Gather and analyse business data requirements effectively.
- Manage data quality and address the challenges that come with it.
- Model and analyse data using modern tools and techniques.
- Present and interpret data clearly to support stakeholder communication.
3Course Content
- Module 1: The Business Data Analyst's Role and the CBDA Path
- The analyst's role in supporting organisational decisions.
- Overview of the data analysis lifecycle.
- Why the CBDA credential matters professionally.
- Module 2: Data and Systems Fundamentals
- Types of data found in business environments.
- Data sources and the systems that support business operations.
- Core governance and quality principles.
- Module 3: Planning a Data Analysis Project
- Defining objectives and requirements.
- Collecting data while ensuring accuracy and relevance.
- Building a work plan aligned with business goals.
- Module 4: Managing Data Quality
- The impact of data quality on analysis outcomes.
- Techniques for cleaning and improving data.
- Addressing data integration challenges.
- Module 5: Exploring and Visualising Data
- Exploratory analysis to identify trends and patterns.
- Applying descriptive and statistical analysis tools.
- Designing reports and dashboards, and choosing the right visualisation method (e.g., Power BI, Tableau).
- Module 6: Qualitative and Quantitative Analysis Techniques
- Differences between qualitative and quantitative data.
- Applying qualitative techniques such as coding.
- Using quantitative analysis for trends and predictions.
- Module 7: Turning Analysis Into Decisions
- Analysing business data needs and evaluating performance gaps.
- Supporting strategy development with data insights.
- Building predictive models and applying data mining and basic machine learning techniques.
- Module 8: Running an Analytical Project
- Planning and organising a data analysis project.
- Identifying necessary resources and tools.
- Monitoring workflow and output quality.
- Module 9: Interpreting Results Responsibly
- Linking outcomes to business objectives and identifying opportunities and risks.
- Formulating strategic recommendations from analysis.
- Ethical considerations, confidentiality, and organisational compliance.
- Module 10: Reporting, Presenting, and Handling Pushback
- Preparing clear, objective analysis reports and executive summaries.
- Communicating with diverse stakeholders.
- Managing technical and non-technical questions, objections, and sensitive topics.
- Module 11: Strategic Analysis and Ongoing Development
- Using analysis to support long-term strategic planning and integrate data into decision-making.
- Studying emerging trends in business data analysis.
- Building a sustainable professional development plan and leveraging IIBA resources.
- Module 12: CBDA Exam Preparation
- Understanding the exam structure and IIBA's six knowledge areas.
- Time management and multiple-choice strategies.
- Practicing with sample theoretical and practical questions.