Data Analytics Fundamentals for Business Decision Making Training Course

Course overview

Business teams often have access to operational, customer, financial and project data but struggle to turn it into evidence that supports a decision. Reports may contain inconsistent definitions, manual calculations, misleading charts or metrics that do not answer the question a manager is asking. This course helps participants move from raw business data and ambiguous requests to structured analysis, defensible findings and clear recommendations.

Participants learn a practical analytics workflow: framing a business question, defining measurable KPIs, assessing data quality, preparing tabular data, analysing trends and variation, and communicating results through dashboards and decision-focused narratives. They work with Microsoft Excel, SQL queries and Power BI to calculate metrics, join and filter data, build pivot-based analysis, test assumptions and distinguish correlation from causation. The emphasis is on selecting methods that fit routine business decisions rather than applying complex statistical models without context.

Teaching combines instructor demonstrations, guided tool practice and a continuous business case involving sales, service and operational performance data. Participants produce an analysis pack containing a problem statement, KPI definitions, cleaned dataset logic, documented calculations, Power BI dashboard and recommendation briefing. This provides a reusable template for analysing a live departmental issue after the course.

The course is suited to professionals who already work with reports, spreadsheets or business systems and now need a more disciplined, repeatable approach to analysing data for management decisions. It is particularly valuable where analysts and business stakeholders need to agree on what the numbers mean before action is approved.

Course objectives

By the end of this course, participants will be able to:

• Frame business questions as measurable analytical objectives with defined decision criteria
• Create KPI definitions that specify formulas, time periods, owners and source systems
• Profile datasets for missing values, duplicates, outliers and inconsistent categories
• Prepare analysis-ready tables using Excel cleaning functions and SQL filtering logic
• Calculate descriptive statistics, growth rates, variances and segment-level performance measures
• Write SQL queries using SELECT, WHERE, GROUP BY, JOIN and aggregate functions
• Build an interactive Power BI dashboard with measures, slicers and decision-relevant visuals
• Produce a documented recommendation briefing that links findings, assumptions, risks and actions

Benefits of attending

Target competencies

Who should attend

• Business Analysts — who need to turn stakeholder questions into evidence-based recommendations
• Operations Managers — who monitor service, capacity, quality and process performance
• Finance Analysts — who explain budget variances and commercial performance using reliable metrics
• Marketing Analysts — who assess campaign, customer segment and channel results
• Project Managers — who need to interpret delivery, resource and risk data for governance decisions
• Reporting Specialists — who want to progress from recurring reports to structured business analysis

Requirements and prerequisites

Participants should be comfortable using a computer, managing files and performing basic spreadsheet tasks such as entering formulas, sorting, filtering and reading tables. Familiarity with business measures such as revenue, cost, volume, percentage change or service levels is helpful, as is experience working with reports or operational data. No prior SQL, Power BI, statistics, programming or database administration experience is required. This is a fundamentals course for professionals with workplace data exposure; complete beginners should expect guided practice with formulas, queries and visualisation tools before applying them to a business case.

Training methodology

The instructor introduces each stage of the analytics workflow through short demonstrations, then participants apply it to a connected business dataset in Excel, SQL Server Management Studio and Power BI Desktop. Exercises include defining KPIs for a management request, correcting data-quality defects, writing queries, checking calculations and selecting visuals for an executive audience. Small-group reviews test whether findings are supported by the data and whether recommendations are actionable. The final session is an application-planning workshop in which participants adapt the course analysis pack to a real workplace decision.

Course outline

Day 1: Business Questions, Metrics and Data Sources

• The business analytics lifecycle from decision request to recommendation
• Converting stakeholder questions into analytical objectives
• Defining leading, lagging and diagnostic KPIs
• Writing metric definitions with numerator, denominator and timeframe
• Identifying source systems, data owners and refresh frequency
• Distinguishing operational, financial, customer and project data
• Documenting assumptions and decision constraints

Workshop: Participants convert a management request about declining performance into an analysis charter with decision question, KPIs, data sources and assumptions.

Day 2: Data Quality and Spreadsheet Analysis

• Data profiling for completeness, validity, uniqueness and consistency
• Detecting duplicates, missing values and category mismatches
• Using Excel tables, filters and conditional formatting for inspection
• Applying XLOOKUP, IF, COUNTIFS and SUMIFS for business analysis
• Cleaning dates, text fields and numeric values with Excel functions
• Building PivotTables and PivotCharts for segment analysis
• Calculating percentages, growth rates, averages and variance measures

Workshop: Participants clean a flawed sales and service extract, build a PivotTable analysis and record the data-quality rules applied.

Day 3: SQL for Business Data Retrieval

• Relational tables, primary keys and foreign keys
• Writing SELECT statements with aliases and calculated fields
• Filtering records with WHERE, IN, BETWEEN and LIKE
• Summarising measures with GROUP BY and aggregate functions
• Joining customer, transaction and operational tables
• Using CASE expressions to create analytical categories
• Validating query results against business rules and control totals

Workshop: Participants write and validate SQL queries that combine customer, order and service data to produce a monthly performance extract.

Day 4: Interpretation and Power BI Visualisation

• Choosing charts for comparison, trend, distribution and contribution
• Recognising misleading scales, aggregation errors and inappropriate chart types
• Interpreting variation, seasonality, outliers and segment differences
• Distinguishing correlation, causation and confounding factors
• Loading and relating tables in Power BI Desktop
• Creating DAX measures for totals, ratios and period comparisons
• Designing report pages with slicers, drill-through and visual hierarchy

Workshop: Participants build a Power BI dashboard that highlights performance trends, priority segments and exceptions requiring management attention.

Day 5: Recommendations and Analytics Application

• Structuring findings from observation to business implication
• Quantifying uncertainty, limitations and data-confidence levels
• Using CRISP-DM to document an end-to-end analytics approach
• Prioritising actions by impact, feasibility and evidence strength
• Creating executive-ready dashboard annotations and narrative headlines
• Presenting recommendations with supporting metrics and assumptions
• Planning data governance, refresh ownership and follow-up measures

Workshop: Participants complete and present an analysis pack containing their dashboard, findings, recommendation briefing and a 30-day workplace application plan.

Tools & standards covered

Microsoft Excel, Microsoft Power BI Desktop, SQL Server Management Studio, CRISP-DM

A typical training day

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

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions