Professional training course · AF-032
Business Intelligence & Analytics for Finance Professionals
Finance functions are increasingly expected to deliver more than accurate accounting records and historical financial reports. Modern finance professionals must transform…
- 5 daysClassroom
- 13Upcoming dates
- 6Cities
- £2,250Fees from
Course overview
Why Attend
Finance functions are increasingly expected to deliver more than accurate accounting records and historical financial reports. Modern finance professionals must transform large volumes of financial and operational information into meaningful insights that support profitability, cost control, financial planning, risk management, and strategic decision-making.
However, financial information is often distributed across enterprise resource planning (ERP) systems, accounting applications, spreadsheets, budgeting platforms, and operational databases. Fragmented data, inconsistent reporting definitions, repetitive manual processes, and limited analytical capabilities can prevent finance teams from providing timely and reliable management information.
Business intelligence (BI) and financial analytics address these challenges by combining data integration, financial modelling, performance measurement, interactive visualisation, and analytical techniques. These capabilities enable finance professionals to monitor financial results, investigate variances, identify emerging trends, improve forecasts, and communicate insights more effectively.
The Business Intelligence & Analytics for Finance Professionals course provides participants with a practical framework for applying business intelligence and data analytics to financial management. Participants explore financial data preparation, data modelling, KPI development, profitability analysis, budgeting analytics, forecasting, dashboard design, and management reporting.
The programme introduces practical applications of Microsoft Excel, Power Query, Power Pivot, and Microsoft Power BI, alongside financial analytical techniques and responsible use of predictive analytics.
Through hands-on exercises and realistic financial datasets, participants develop the ability to build reliable financial reporting solutions, analyse business performance, and translate analytical findings into actionable management recommendations.
Professional Problems This Course Is Designed to Solve
Fragmented financial information: Integrating data from accounting systems, ERP platforms, spreadsheets, and operational sources into consistent analytical datasets.
Time-consuming financial reporting: Reducing repetitive data preparation, reconciliation, and report production through automated data transformation and refreshable reporting models.
Limited visibility of financial performance: Developing interactive dashboards that provide timely insights into profitability, revenue, expenditure, cash flow, and working capital.
Weak budget and forecast analysis: Applying financial analytics to investigate variances, evaluate planning assumptions, and improve forecasting decisions.
Inconsistent financial KPIs: Establishing standard definitions, calculation methods, reporting responsibilities, and performance targets across departments.
Difficulty identifying financial trends and risks: Using analytical techniques to detect unusual transactions, changing cost patterns, liquidity pressures, and performance deterioration.
Poor communication of financial insights: Transforming complex financial data into clear visualisations, executive reports, and decision-focused recommendations.
Course Methodology
The programme combines instructor-led discussions, financial analytics demonstrations, practical data preparation exercises, business intelligence workshops, dashboard development activities, and financial performance case studies.
Participants work with realistic datasets covering general ledger transactions, sales revenue, operating expenses, budgets, accounts receivable, accounts payable, and cash flow information.
Hands-on activities use Excel-based analytical techniques, Power Query, Power Pivot, and Power BI concepts to demonstrate financial data integration, analytical modelling, performance calculations, and interactive reporting.
The training emphasises data accuracy, analytical interpretation, financial relevance, and the practical application of business intelligence tools to everyday finance responsibilities.
Course Objectives
By the end of this course, participants will be able to:
Explain the role of business intelligence and analytics in modern financial management
Identify financial data sources and evaluate data quality requirements
Prepare, clean, consolidate, and transform financial datasets
Understand financial data modelling and relationships between accounting and operational information
Develop meaningful financial KPIs and performance measurement frameworks
Apply analytical techniques to revenue, cost, profitability, and working capital information
Perform budget-versus-actual analysis and financial variance investigation
Apply forecasting and scenario analysis to financial planning
Build interactive financial dashboards and management reports
Use Excel, Power Query, Power Pivot, and Power BI for financial analysis
Evaluate data governance, reporting accuracy, and access control considerations
Communicate financial insights and recommendations to management stakeholders
Target Audience
This course is suitable for:
Finance managers and financial controllers
Financial planning and analysis professionals
Management accountants and senior accountants
Financial analysts and business finance partners
Budget managers and cost control specialists
Treasury and working capital professionals
Financial reporting and management information specialists
Internal auditors and financial risk analysts
Business intelligence professionals supporting finance functions
Finance transformation and financial systems professionals
Target Competencies
Participants will develop competencies in:
Financial business intelligence
Financial data preparation and integration
Financial data modelling
Financial KPI design and measurement
Revenue and profitability analytics
Budget and variance analysis
Financial forecasting and scenario modelling
Working capital and cash flow analytics
Interactive financial dashboard development
Data-driven financial decision-making
Course outline
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1Day 1: Business Intelligence Foundations and Financial Data Preparation
Understanding business intelligence, descriptive analytics, diagnostic analytics, predictive analytics, and their applications within finance functions
Identifying financial data sources, including ERP systems, general ledgers, budgeting platforms, banking records, and operational databases
Evaluating financial data quality through completeness, accuracy, consistency, timeliness, and reconciliation requirements
Applying Power Query techniques to import, clean, standardise, merge, and consolidate financial datasets
Understanding financial data structures, chart of accounts mapping, reporting dimensions, and relationships between financial and operational information
Practical workshop: Preparing an integrated financial dataset from general ledger, budget, and operational records for management reporting
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2Day 2: Financial Data Modelling, KPI Development and Profitability Analytics
Developing financial data models using fact tables, dimension tables, account classifications, reporting periods, and organisational hierarchies
Understanding Power Pivot and Power BI data modelling principles, including table relationships, calculated measures, and filter behaviour
Establishing financial KPIs covering revenue growth, gross margin, operating margin, return on investment, cost efficiency, and financial productivity
Applying financial analysis techniques to evaluate profitability by product, customer, department, business unit, and operating segment
Using DAX concepts and analytical calculations to develop financial ratios, period comparisons, cumulative results, and performance measures
Practical exercise: Building a financial performance model with revenue, expenditure, profitability, and departmental KPI calculations
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3Day 3: Budget Analytics, Forecasting and Financial Performance Evaluation
Integrating budget, actual, and forecast data to establish consistent financial performance reporting structures
Performing budget-versus-actual analysis using absolute variances, percentage variances, financial trends, and operational drivers
Applying diagnostic analytics to investigate revenue shortfalls, expenditure increases, margin deterioration, and departmental performance differences
Developing financial forecasting models using historical trends, business drivers, assumptions, and rolling forecast techniques
Applying sensitivity and scenario analysis to evaluate changes in sales, pricing, costs, inflation, and financial performance
Practical workshop: Developing a financial planning and variance analysis model with forecast scenarios, performance indicators, and management explanations
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4Day 4: Working Capital Analytics, Financial Risk Indicators and Interactive Dashboards
Analysing accounts receivable through ageing reports, collection trends, overdue balances, customer concentration, and days sales outstanding
Evaluating accounts payable, supplier payment patterns, cash conversion cycles, and working capital efficiency
Developing cash flow analytics to monitor liquidity movements, operating cash generation, payment commitments, and short-term funding requirements
Identifying unusual financial patterns and potential reporting exceptions through trend analysis, transaction comparisons, and exception indicators
Designing interactive financial dashboards using Power BI or Excel with charts, KPI cards, slicers, filters, and financial performance summaries
Dashboard workshop: Creating an interactive financial management dashboard covering profitability, working capital, budget performance, and liquidity indicators
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5Day 5: Financial Reporting Automation, Data Governance and Analytical Decision-Making
Developing automated financial reporting workflows using Power Query refresh processes, reusable data models, and standardised reporting templates
Applying financial data governance principles covering data ownership, access permissions, confidentiality, validation, and reporting consistency
Evaluating the practical use of predictive analytics and artificial intelligence in financial forecasting, anomaly identification, and management reporting
Communicating financial insights through executive dashboards, analytical commentary, visual storytelling, and decision-focused financial recommendations
Establishing a financial business intelligence improvement roadmap covering technology, analytical capabilities, reporting processes, and performance measurement
Capstone exercise: Developing and presenting an Integrated Financial Business Intelligence Solution incorporating data preparation, financial modelling, KPI analysis, budget comparisons, working capital analytics, interactive dashboards, and management recommendations
Schedule
Dates and fees
13 upcoming dates in 6 cities. Fees are per delegate; bring colleagues and every seat is discounted.
No dates in this city right now. Request a quotation and we will suggest the nearest date.
Questions
Frequently asked questions
How long is the Business Intelligence & Analytics for Finance Professionals course?
The course runs over 5 days of classroom training, usually Monday to Friday.
When is the next Business Intelligence & Analytics for Finance Professionals course?
The next public date is 21 - 25 Dec 2026 in Kuala Lumpur. There are 13 upcoming dates in total.
Where is this course held?
Upcoming sessions run in Kuala Lumpur, Dubai, Istanbul, Rome, Vienna, Barcelona.
How much does the course cost?
Fees start from £2,250 per delegate, depending on the city. Fees include tuition and course materials.
Do participants receive a certificate?
Yes. Delegates who complete the course receive a London Leadership Management Innovation certificate of completion.
Can this course be delivered in-house for our team?
Yes. LLMI can tailor and deliver this course privately for your organisation at your premises or in one of our training cities.
Course information last updated 14 November 2026.
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