Financial Data Analytics with Excel Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Financial Analysts, FP&A Analysts and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-FM-162

Before you join: Participants should be comfortable using Excel worksheets, formulas, sorting, filtering and basic charts.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Finance teams often spend too much time cleaning exports, checking formulas and reconciling inconsistent reports before they can explain what performance means. General ledger extracts, budgets, sales data, payroll files and cash positions frequently sit in separate workbooks with different account codes, dates and levels of detail. This creates reporting delays, weak audit trails and avoidable risk when management decisions depend on trend analysis, forecasts and variance explanations.

This course teaches finance professionals to build controlled, refreshable Excel analyses from raw financial data. Participants work with Excel Tables, Power Query, PivotTables, Power Pivot, dynamic-array formulas and data models to prepare data, analyse results and produce management-ready outputs. The course covers driver-based forecasting, rolling cash forecasting, flexible budgets, price-volume-mix analysis, financial ratio analysis, anomaly screening, scenario modelling and sensitivity testing. Participants also learn how to document assumptions, test calculations and apply practical workbook controls.

Teaching combines short technical briefings with instructor demonstrations, finance cases, group analysis and individual workbook development. Cases reflect reporting and planning work commonly found in banks, public institutions, NGOs, multinationals and corporate finance functions. Participants leave with a reusable financial analytics workbook structure, including data-preparation queries, reporting layouts, forecast schedules, variance-analysis models and a control checklist. The final application plan identifies a priority reporting or planning process to improve using the methods taught.

The course suits finance professionals who already use Excel for reporting, budgeting, planning or financial analysis and need more reliable methods for handling larger, more complex data sets. It is particularly relevant where teams need to reduce manual reporting effort while improving the quality, traceability and decision value of financial information.

What you will be able to do

  • Structure financial data using Excel Tables, data lineage and controlled workbook architecture
  • Prepare refreshable finance data sets with Power Query transformations and reconciliation checks
  • Build auditable calculations using XLOOKUP, dynamic arrays, LET and formula-auditing methods
  • Analyse financial performance through PivotTables, data models and DAX measures
  • Develop driver-based forecasts, rolling cash forecasts and working-capital schedules
  • Explain budget and actual movements using flexible budgets, bridges and price-volume-mix analysis
  • Test financial assumptions through scenarios, sensitivity analysis, Solver and Monte Carlo simulation
  • Establish workbook controls using validation, protection, review checklists and version conventions

Benefits of attending

For you

  • Reduce manual effort when preparing recurring financial reports and analyses
  • Build auditable forecast and variance models suitable for management review
  • Identify data-quality issues before they affect reported financial results
  • Explain financial movements with quantified drivers rather than unsupported commentary
  • Present stronger evidence for planning, investment and cost-management decisions

For your organisation

  • Shorten reporting cycles through refreshable data-preparation and reporting processes
  • Improve confidence in management information through documented controls and reconciliations
  • Strengthen forecast accuracy by linking financial outcomes to operational drivers
  • Focus management attention on material variances, exceptions and emerging cash risks
  • Create reusable Excel reporting standards across finance teams and business units

Course modules

10 modules over 5 days

Participants can define an analytical question and structure a controlled Excel workbook for financial reporting.

  • Analytical question framing using decision, metric, period and data-owner definitions
  • Excel Tables structured references for controlled financial data ranges
  • Data types, date serials and sign conventions reconciled before calculation
  • Source-to-report data lineage documented with owner, refresh frequency and controls
  • Materiality thresholds distinguish decision-relevant exceptions from routine data variation
  • Workbook architecture separating inputs, calculations, outputs and documentation sheets

Participants can import, clean, combine and reconcile finance data through repeatable Power Query processes.

  • Power Query imports CSV, workbook and folder-based monthly finance extracts
  • Query steps standardise headers, data types, currencies and account codes
  • Append and merge queries combine ledger, budget and master-data tables
  • Duplicate detection and null profiling expose incomplete transaction records
  • Reconciliation checks compare record counts, totals and control accounts
  • Refreshable audit trail records transformations, assumptions and source exceptions

Participants can build transparent financial calculations using modern Excel functions and formula-review methods.

  • SUMIFS, COUNTIFS and AVERAGEIFS summarise transactions by financial dimensions
  • XLOOKUP retrieves chart-of-accounts mappings with explicit missing-value treatment
  • Dynamic arrays filter, sort and spill analysis without copied formulas
  • LET functions simplify multi-stage calculations and improve formula auditability
  • IFERROR handling distinguishes absent data from calculation and reference errors
  • Formula auditing traces precedents, dependents and inconsistent calculation logic

Participants can create interactive financial reports that present trends, variances and transaction-level evidence.

  • PivotTables summarise revenue, cost and margin by management dimensions
  • Slicers and timelines filter period, entity, product and cost-centre views
  • Calculated fields and measures separate operational metrics from source data
  • Drill-through analysis validates unusual balances against underlying transactions
  • PivotChart selection matches variance, trend and composition analysis requirements
  • Reusable dashboard layouts retain clear definitions, filters and reporting dates

Participants can build relational Excel data models and calculate consistent financial measures using DAX.

  • Data Model relationships connect fact tables to shared dimensions
  • Star schema design separates transactions, calendars, accounts and organisational hierarchies
  • Power Pivot measures calculate actuals, budget, variance and prior-period comparisons
  • DAX CALCULATE modifies filter context for controlled financial measures
  • Calendar tables support month-to-date, year-to-date and rolling-period reporting
  • Relationship diagnostics identify duplicate keys, orphan records and ambiguous joins

Participants can construct driver-based financial forecasts and rolling cash models with stated assumptions.

  • Driver-based revenue forecasts link volume, price, mix and conversion assumptions
  • 13-week rolling cash forecasts combine receipts, payroll, payables and debt service
  • Working-capital schedules model receivables days, inventory turns and payable terms
  • FORECAST.ETS estimates seasonal series while exposing forecast confidence intervals
  • Assumption registers record source, rationale, owner, review date and sensitivity
  • Forecast-versus-actual bridges isolate volume, rate, timing and mix effects

Participants can quantify performance movements and prepare evidence-based explanations for management decisions.

  • Flexible budgets restate expected cost at actual activity levels
  • Price-volume-mix analysis explains revenue and gross-margin movements between periods
  • Waterfall bridges communicate budget, actual and forecast movement drivers
  • Variance thresholds prioritise investigation using materiality and controllability criteria
  • Root-cause trees separate commercial, operational, timing and accounting explanations
  • Management commentary links quantified variance evidence to corrective action

Participants can assess financial performance, identify anomalies and document analytical review conclusions.

  • Common-size statements compare income-statement and balance-sheet composition across reporting periods
  • Ratio analysis calculates liquidity, profitability, efficiency and solvency indicators
  • Benford's Law screens transaction populations for unusual leading-digit distributions
  • Outlier tests use z-scores, percentile bands and exception thresholds
  • Period-end trend analysis identifies cutoff risks and unusual journal patterns
  • Analytical review documentation records expectation, evidence, conclusion and follow-up

Participants can evaluate financial uncertainty and communicate scenario implications to decision-makers.

  • Scenario Manager compares base, downside and upside assumption sets
  • Data Tables test one-way and two-way sensitivity assumptions
  • Excel Solver optimises resource allocation subject to financial constraints
  • Monte Carlo simulation estimates distributions for uncertain revenue and cost drivers
  • Tornado charts rank variables by their effect on valuation
  • Decision briefs state assumptions, ranges, downside exposure and recommended actions

Participants can apply spreadsheet controls and plan a focused improvement to a finance reporting process.

  • Control matrices assign data ownership, review evidence and approval responsibilities
  • Protected sheets, locked formulas and input validation prevent accidental changes
  • Version-control conventions identify reporting period, preparer and approved release
  • Peer review checklists test formulas, reconciliations, labels and presentation
  • Management-ready outputs distinguish reported facts, estimates and management assumptions
  • Personal application plans specify a priority model, data source and sponsor

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Financial analytics workbook architecture template
  2. Power Query data-preparation workflow
  3. Rolling cash forecast model
  4. Budget variance and bridge analysis template
  5. Financial workbook control checklist
  6. Personal reporting improvement plan

Who should attend

  • Financial Analysts — build faster, more traceable analyses from finance and operational data
  • FP&A Analysts — improve forecasting, budgeting and management performance reporting
  • Management Accountants — explain variances and prepare controlled monthly reporting packs
  • Finance Managers — review financial trends, assumptions and exception reporting with confidence
  • Treasury Analysts — construct rolling cash forecasts from receipts, payments and debt schedules
  • Internal Auditors — assess spreadsheet controls, data quality and analytical review evidence

Skills and tools covered

Financial data preparationExcel financial modellingVariance analysisCash flow forecastingScenario analysisWorkbook controls

Tools and standards

Microsoft Excel, Power Query, Power Pivot, Excel Solver

How the course runs

Training methodology

The course uses short instructor briefings followed by guided Excel demonstrations and finance-focused case work. Participants prepare source data, construct formulas, create PivotTable reports and develop forecast and variance models using realistic reporting scenarios. Group exercises examine data-quality failures, exception patterns and management-reporting choices. Simulations test scenarios, cash positions and decision trade-offs under changing assumptions. Instructor feedback focuses on formula design, data controls, reconciliation evidence and presentation quality. Participants finish by preparing an application plan for a reporting, forecasting or planning process in their own role.

Requirements and prerequisites

Participants should be comfortable using Excel worksheets, formulas, sorting, filtering and basic charts. They should understand core finance concepts such as income statements, balance sheets, cash flow, budgets, actuals and variances. Experience preparing monthly reports, forecasts, reconciliations or management information is helpful. Participants do not need prior experience with Power Query, Power Pivot, DAX, VBA, programming, statistics software or database administration. Advanced accounting qualifications are not required, although participants should be able to interpret common financial measures and account categories.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

You should be able to use standard formulas, sort and filter data, and work with basic worksheets. The course teaches Power Query, Power Pivot, DAX and advanced analysis methods from the ground up, but it moves quickly through basic Excel tasks.

Bring a laptop with a current desktop version of Microsoft Excel where possible, as several features are not available in browser-only Excel. You may also bring a non-confidential reporting challenge or sample data structure from your role for use during application planning.

It is designed for financial analysts, FP&A professionals, management accountants, finance managers, treasury analysts and internal auditors. Participants benefit most when they regularly prepare reports, forecasts, budgets, reconciliations or management information.

General Excel courses usually focus on software features, while financial modelling courses commonly focus on valuation or corporate-finance models. This course concentrates on analysing finance data, producing controlled reports, explaining variances and improving forecasting processes.

You can use the methods to replace manual monthly consolidation, create refreshable budget-versus-actual reports, improve cash forecasting or investigate unusual transactions. The templates and control methods are designed for adaptation to your own chart of accounts, reporting calendar and management requirements.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. Time is divided between instructor explanation, Excel demonstrations, individual analysis, group case work, review discussions and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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