Business analysts frequently work with information stored across multiple datasets, making accurate data retrieval and logical processing essential skills. This module introduces advanced Excel techniques that help learners connect data, automate analysis, and improve efficiency in business reporting. Learners will begin by exploring LOOKUP functions and understanding how they enable dynamic retrieval of information from different data sources. The module then focuses on logical functions such as IF, AND, and OR, helping learners apply business rules and perform conditional analysis in a structured and repeatable way. Together, these functions provide a strong foundation for building spreadsheets that support complex analytical requirements. As the module progresses, learners will combine data retrieval and logical analysis to create integrated workflows that automate common business tasks and improve consistency. They will also examine how AI can support spreadsheet development through formula generation, conversational analysis, and workflow enhancement. By the end of the module, learners will be able to design more efficient spreadsheet solutions, reduce manual effort, and generate business insights with greater accuracy and confidence.

Automation plays an increasingly important role in improving productivity and reducing repetitive work within business analysis. This module introduces the concepts behind Excel automation and macros, helping learners understand how common spreadsheet activities can be completed more efficiently through structured automation. Learners will explore the purpose of macros, how automation supports consistency, and where automated processes can add value to analytical workflows. The module examines macro recording techniques and demonstrates how routine spreadsheet activities can be standardised to reduce manual effort and improve operational efficiency. Attention is also given to governance considerations, automation risks, and the fundamentals of VBA, providing learners with an awareness of the controls needed when introducing automation into business processes. The module further explores how AI can support script generation, workflow design, and automation development. Learners will gain insight into intelligent workflow orchestration and emerging automation approaches that combine human oversight with AI-assisted capabilities. By understanding both the opportunities and limitations of spreadsheet automation, learners will be better prepared to identify efficiency improvements while maintaining quality, reliability, and business control.

High-quality analysis depends on high-quality data. This module focuses on practical techniques for identifying, correcting, and transforming data so that it can be used confidently to support business decisions. Learners begin by exploring common data quality challenges and understanding how inaccurate, incomplete, or inconsistent information can affect analytical outcomes. The module introduces proven methods for cleaning and standardising datasets, helping learners improve accuracy and reliability before analysis begins. Learners will also examine techniques for restructuring data into formats that better support reporting, trend analysis, and performance measurement. These skills are essential when working with information from multiple sources or preparing data for visualisation and dashboarding tools. In addition, the module explores how AI can assist with data profiling, anomaly identification, cleaning recommendations, and transformation processes. Learners will discover how intelligent data preparation workflows can improve efficiency while maintaining appropriate analytical oversight. The module concludes with an introduction to AI-native data pipelines and continuous data intelligence, demonstrating how modern organisations maintain data quality and readiness at scale to support faster and more informed decision-making.

Effective dashboards help stakeholders understand information quickly and make better decisions. This module introduces the principles of dashboard design and explores how information can be structured to maximise clarity, relevance, and usability. Learners will understand how visual hierarchy influences attention and how effective layouts support decision-making. The module examines visualisation best practices and introduces key concepts from Gestalt thinking to help learners create reports that are intuitive and easy to interpret. Learners will explore how colour, spacing, grouping, and visual relationships influence understanding and communication. The module also highlights common dashboard design mistakes and reporting anti-patterns that can reduce the effectiveness of business insights. Learners will discover how AI can support dashboard improvement by reviewing designs, identifying usability concerns, and recommending enhancements. The module concludes by exploring AI-native dashboards and conversational analytics experiences that allow users to interact with information in more flexible and insightful ways. By applying both design principles and analytical thinking, learners will be able to create dashboards that communicate meaningful business insights clearly and effectively.

Power BI is a widely used business intelligence platform that enables analysts to transform data into interactive and actionable insights. This module introduces the core capabilities of Power BI and demonstrates how it supports modern business analysis, reporting, and decision-making activities. Learners will explore how data models and relationships provide the foundation for scalable reporting solutions. The module introduces DAX fundamentals, helping learners create business calculations and performance measures that provide deeper analytical value. Attention then shifts to visualisation and dashboard creation, where learners will build reports designed to support stakeholder needs and encourage effective information exploration. The module also examines publishing, sharing, governance, and collaboration features that help organisations manage reporting environments successfully. Learners will discover how AI-powered capabilities can accelerate insight generation, identify trends, and enhance analytical interpretation. Finally, the module explores emerging AI-native business intelligence approaches, including conversational analytics and adaptive reporting experiences. By the end of the module, learners will have a practical understanding of how Power BI supports data-driven decision-making and effective communication of business performance.

Tableau enables business analysts to explore information visually and uncover insights that support better decision-making. This module introduces the fundamentals of Tableau and demonstrates how visual analytics can help analysts identify patterns, trends, and opportunities more effectively. Learners will begin by exploring Tableau’s approach to data visualisation and analytical thinking. The module explains how data models and calculated fields support flexible analysis and enable users to create meaningful business metrics. Through practical examples, learners will understand how Tableau helps transform raw information into clear visual stories that support stakeholder understanding. The module also examines AI-assisted capabilities, including conversational analytics, automated insight discovery, and intelligent exploration tools. Learners will explore how features such as Tableau Pulse and natural language interactions can make analytical work more accessible and efficient. The module concludes by introducing AI-native analytics approaches that proactively deliver relevant insights and support continuous business awareness. By combining visual exploration, structured analysis, and AI-assisted discovery, learners will be prepared to use Tableau effectively within modern business analysis environments.

The value of analysis depends on how effectively insights are communicated. This module focuses on transforming analytical findings into compelling business narratives that help stakeholders understand information and make informed decisions. Learners will explore the importance of insight storytelling and the role it plays in successful business analysis. The module introduces approaches to executive communication, including the Pyramid Principle and structured narrative techniques commonly used to present complex information clearly and concisely. Learners will discover how to move beyond charts and metrics by connecting data to business context, implications, and recommended actions. Particular attention is given to converting dashboard findings into meaningful stories that support strategic decision-making. Learners will also examine how AI can enhance reporting through content generation, insight summarisation, and personalised communication. The module explores emerging approaches to adaptive reporting that tailor information to different stakeholder needs while maintaining analytical accuracy and clarity. By the end of the module, learners will be able to communicate insights with greater confidence, influence business discussions, and ensure analytical findings lead to meaningful action.

This module provides learners with an opportunity to consolidate and apply the skills developed throughout the course in a practical business context. Through scenario-based activities and assessment tasks, learners will demonstrate their ability to collect, prepare, analyse, visualise, and communicate business data effectively. The assessment draws upon concepts covered across the course, including Pivot Tables, LOOKUP functions, spreadsheet automation, data cleaning, dashboard design, Power BI, Tableau, and executive reporting. Learners will be expected to apply structured analytical approaches, interpret findings accurately, and present recommendations supported by evidence. The module also encourages the responsible use of AI throughout the analytical process. Learners will evaluate how AI can support data preparation, formula generation, insight discovery, reporting, and communication while maintaining professional judgement and accountability. By completing the assessment, learners will strengthen their ability to transform raw data into meaningful business insights and communicate those findings in ways that support informed decisions, stakeholder engagement, and organisational performance.