Global Learning for Operational Leaders
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0 sessionsIntroduction
Course overview
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.
What you will achieve
Learning objectives
- 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
Who should attend
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
Methodology
Learning approach
- 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.
Complete course outline
Five focused days of learning and application
The timings provided are estimates and may vary depending on the number of participants and the discussions taking place during the sessions. They are indicative only and do not constitute a binding commitment.
Day 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
- Coffee break
- Applying Power Query techniques to import, clean, standardise, merge, and consolidate financial datasets (continued)
- 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
Day 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
- Coffee break
- 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
Day 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
- Coffee break
- Developing financial forecasting models using historical trends, business drivers, assumptions, and rolling forecast techniques (continued)
- 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
Day 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
- Coffee break
- 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
Day 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
- Coffee break
- Evaluating the practical use of predictive analytics and artificial intelligence in financial forecasting, anomaly identification, and management reporting (continued)
- 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
FAQ
Frequently asked questions
What does Business Intelligence & Analytics for Finance Professionals (AF-032) cover?
This course covers Accounting and Finance through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The course schedule and fee are available on request. Contact Aractech for current availability and a quotation.
Who should attend this course?
This course is suitable for:, Finance managers and financial controllers, Financial planning and analysis professionals
Is bilingual course delivery available?
Yes. All course materials and presentations are provided in English, while bilingual explanation and discussion support may be available depending on the selected location and trainer availability. For example, when attending a course in Istanbul, you may request a Turkish-speaking trainer to explain the English course content in Turkish. Arabic explanation support may also be requested at this location. Other languages are available in selected cities. You can choose your preferred language support as an optional preference during registration.
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
The schedule and fee, including any available delivery options, are available on request. Contact Aractech for details.
Where are classroom sessions delivered?
Classroom venues are confirmed in the schedule panel for each published session.
How long is the training programme?
The programme runs for five days, with up to five training hours per day, from 9:00 AM to 2:00 PM. Each programme includes a total of 25 training hours.
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