Data Analytics for Business Analysts Training Course

Course overview

Business analysts are increasingly expected to substantiate requirements, prioritise change requests, diagnose process issues and measure benefits with data rather than stakeholder opinion alone. This course equips analysts to work confidently from raw operational data to a decision-ready insight: defining the business question, testing data quality, identifying patterns, and explaining what the evidence means for a process, product or service. It is designed for analysts who need to bridge business stakeholders and data specialists without becoming full-time data scientists.

Participants learn a practical analytics workflow using Microsoft Excel, SQL and Microsoft Power BI. They translate business objectives into measurable questions, define KPIs and calculation rules, map data requirements to source systems, profile and clean datasets, write SQL queries, apply descriptive statistics, and build dashboards that support action. The course also covers analytical techniques used in business analysis, including segmentation, trend analysis, root-cause analysis, funnel analysis and before-and-after benefit measurement.

Teaching combines instructor-led demonstrations with realistic case material based on customer operations, service performance and process improvement. Participants work through the lifecycle of an analytics assignment: producing a KPI definition sheet, a data-quality assessment, SQL query outputs, an analysis workbook and a Power BI dashboard. They leave with a documented analytics pack and a 90-day application plan that can be adapted to a live initiative in their organisation.

The course is particularly valuable for business analysts supporting digital transformation, operational improvement, CRM, finance, customer service or product change programmes. Managers benefit from analysts who can ask better questions of data teams, recognise weak evidence early and present findings in terms that decision-makers can act on.

Course objectives

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

• Translate a business problem into testable analytical questions, measures and decision criteria
• Define KPIs using calculation logic, targets, owners, reporting frequency and data-source rules
• Profile a dataset to identify completeness, validity, duplication, consistency and timeliness issues
• Write SQL SELECT queries using joins, filters, aggregations, CASE statements and grouped calculations
• Apply descriptive statistics, segmentation and trend analysis to identify meaningful operational patterns
• Construct a traceable data-requirements specification linking business measures to source-system fields
• Build an interactive Microsoft Power BI dashboard with calculated measures, filters and decision-focused visuals
• Present an evidence-based recommendation with assumptions, limitations, risks and proposed actions

Benefits of attending

Target competencies

Who should attend

• Business Analysts — who need to use data to validate requirements, diagnose issues and recommend change
• Senior Business Analysts — who lead evidence-based analysis across complex process or digital initiatives
• Systems Analysts — who translate operational data and system behaviour into actionable business findings
• Product Owners — who prioritise product improvements using customer, usage and service-performance data
• Process Improvement Analysts — who measure bottlenecks, defects, cycle times and realised benefits
• Project Managers — who need credible KPI baselines and benefits measures for change programmes

Requirements and prerequisites

Participants should be comfortable using spreadsheets for sorting, filtering, simple formulas and charts, and should understand basic business-process terms such as stakeholder, requirement, KPI and workflow. Experience of business analysis, operations, product delivery or reporting is helpful because exercises use realistic business scenarios. No previous SQL, Power BI, statistics or programming experience is required; these are taught from first principles. Complete beginners should expect a practical introduction rather than advanced data science, machine learning or database administration. A laptop able to run Microsoft Excel and Power BI Desktop is strongly recommended.

Training methodology

An experienced instructor leads short, focused explanations followed by guided work in Excel, SQL and Power BI. A running business case supplies operational, customer and process data that participants profile, query and turn into decision evidence. Exercises include KPI-definition workshops, data-quality triage, query-building labs, dashboard critique and stakeholder read-outs. Small groups compare analytical choices and challenge unsupported conclusions. On the final day, each participant assembles an analytics pack and identifies a live workplace question to address during the following 90 days.

Course outline

Day 1: Framing business questions and measures

• The business analyst analytics lifecycle from decision question to recommendation
• Distinguishing business outcomes, drivers, metrics and operational measures
• SMART analytical questions and hypotheses
• KPI definition templates and calculation rules
• Baseline, target, tolerance and threshold design
• Data requirements elicitation for measures and reports
• Data lineage from business process to source-system field

Workshop: Participants convert a service-performance problem into a KPI catalogue, analytical questions and a field-level data-requirements draft.

Day 2: Data quality and exploratory analysis

• Dataset structure, data types and grain of data
• Completeness, validity, consistency, uniqueness and timeliness checks
• Excel sorting, filtering and conditional formatting for data profiling
• Handling missing values, duplicates and invalid categories
• PivotTables and PivotCharts for exploratory analysis
• Descriptive statistics including mean, median, range and percentiles
• Analytical assumptions, sampling bias and limitations statements

Workshop: Using a customer-service dataset, participants create a data-quality assessment and an initial findings workbook with documented limitations.

Day 3: SQL for business analysis

• Relational tables, primary keys, foreign keys and entity relationships
• SELECT, FROM, WHERE and ORDER BY query structure
• Aggregate functions with GROUP BY and HAVING
• INNER JOIN and LEFT JOIN for combining business data
• CASE expressions for business-rule classification
• Date filtering and period-based calculations
• Query validation against KPI definitions and expected totals

Workshop: Participants write and validate SQL queries to calculate service volumes, resolution rates, customer segments and overdue-case measures.

Day 4: Finding causes, patterns and priorities

• Trend analysis and time-series comparisons
• Segmentation by customer, channel, product and process stage
• Pareto analysis for high-impact issue categories
• Funnel analysis for conversion and workflow drop-off
• Root-cause analysis using five whys and cause-and-effect mapping
• Before-and-after measurement for change initiatives
• Correlation interpretation and the limits of causal claims

Workshop: Teams analyse a declining service-performance case, identify priority drivers and prepare an evidence-backed root-cause narrative.

Day 5: Dashboards, recommendations and application

• Power BI data loading and transformation fundamentals
• Data model relationships and star-schema principles
• Measures and calculated columns for business metrics
• Visual selection for trends, comparisons, composition and exceptions
• Dashboard layout, filters, drill-through and accessibility
• Communicating recommendations, uncertainty and decision implications
• Analytics governance, metric ownership and 90-day application planning

Workshop: Participants build a Power BI decision dashboard and present an analytics pack containing findings, recommendations, assumptions and next actions.

Tools & standards covered

Microsoft Excel, SQL, Microsoft Power BI, BPMN 2.0

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