Business Intelligence Reporting for Business Analysts Training Course

Participants can define report scope, stakeholder responsibilities and controlled requirements boundaries.

• RACI matrices assign reporting decisions, approvals, data ownership and support duties
• Personas capture information needs, technical confidence, time constraints and preferred views
• In-scope and out-of-scope statements prevent uncontrolled report requirement expansion
• MoSCoW prioritisation ranks mandatory, important, desirable and deferred reporting features
• Requirement traceability links business questions, data fields, calculations and visuals
• Assumption logs distinguish confirmed facts from unresolved reporting design decisions

Participants can specify consistent metrics with clear formulae, ownership and interpretation rules.

• KPI trees connect strategic objectives, drivers, measures, targets and actions
• Measure definitions state numerator, denominator, grain, period and source system
• Leading and lagging indicators distinguish predictive signals from recorded outcomes
• Targets, thresholds and tolerances define when management attention is required
• Metric owners approve definitions, changes, exceptions and business interpretation guidance
• KPI catalogues document formulae, dimensions, exclusions, refresh timing and lineage

Participants can identify reporting sources and evaluate their fitness for stated reporting purposes.

• Source system mapping identifies entities, fields, owners, extracts and refresh schedules
• Data profiling measures completeness, uniqueness, validity, consistency and timeliness
• Field-level analysis reveals nulls, duplicates, invalid codes and unexpected distributions
• Business keys distinguish customer, account, transaction, product and organisational identifiers
• Grain analysis establishes the lowest level represented by each source record
• Source-to-target mapping documents transformations, derived fields and reporting destinations

Participants can define data quality rules and reconcile reporting outputs to trusted controls.

• Data quality dimensions assess accuracy, completeness, consistency, timeliness and validity
• Validation rules test mandatory fields, code sets, ranges and referential integrity
• Control totals reconcile record counts, monetary values and quantities between systems
• Exception reports isolate failed records, root causes, owners and resolution status
• Tolerance rules distinguish acceptable rounding differences from material reporting errors
• Issue logs record defect severity, business impact, correction actions and closure evidence

Participants can write and review SQL queries that prepare and validate reporting datasets.

• SELECT statements retrieve named fields from reporting tables and views
• WHERE clauses filter periods, business units, statuses and valid record populations
• INNER and LEFT JOIN operations combine related reporting entities correctly
• GROUP BY and aggregate functions summarise values at defined reporting grain
• CASE expressions classify records into business reporting categories and bands
• Common table expressions improve readability of multi-step reporting query logic

Participants can create dimensional models that support consistent and performant reporting.

• Kimball dimensional modelling separates measurable events from descriptive business context
• Fact tables store transactions, snapshots, balances and measurable process events
• Dimension tables describe dates, customers, products, locations, channels and organisations
• Star schemas simplify report queries, filtering, aggregation and user understanding
• Conformed dimensions provide consistent categories across multiple subject-area reports
• Slowly changing dimensions preserve historical attributes for accurate period reporting

Participants can define time periods, aggregation rules and comparison logic for management reporting.

• Calendar tables support daily, monthly, quarterly, financial-year and fiscal-period reporting
• Reporting grain aligns transaction detail with required management decision frequency
• Period-to-date calculations distinguish month, quarter and year accumulation rules
• Prior-period comparisons reveal variance, growth, decline and seasonal movement
• Rolling periods smooth short-term volatility in service, sales and operational measures
• Snapshot reporting distinguishes point-in-time balances from cumulative transaction activity

Participants can prepare data and configure a Power BI model for governed report creation.

• Power Query steps clean headers, data types, nulls and inconsistent values
• Query parameters control reusable source locations, dates and reporting selections
• Relationship cardinality defines valid one-to-many and many-to-many model connections
• Filter direction choices prevent ambiguous results and unintended cross-table filtering
• Model views document table purpose, key fields and relationship assumptions
• Refresh planning considers source availability, data latency, credentials and report publication

Participants can create DAX measures that calculate and explain core reporting indicators.

• DAX measures calculate aggregations without storing repeated report-level values
• CALCULATE modifies filter context for targeted reporting business rules
• DIVIDE handles ratio calculations and avoids invalid division results
• Time intelligence functions compare current periods with previous reporting periods
• Measure naming conventions distinguish values, ratios, variances and percentage changes
• Calculation validation compares DAX outputs against independently checked control totals

Participants can produce build-ready report specifications and testable acceptance criteria.

• Report specifications define purpose, audience, data scope, measures and refresh timing
• User stories describe reporting needs from named stakeholder roles and decisions
• Given-When-Then acceptance criteria make expected report behaviour testable
• Field specifications identify labels, formats, sources, calculations and drill paths
• Business rules document exclusions, overrides, hierarchy treatment and exception handling
• Non-functional requirements cover performance, accessibility, security and export needs

Participants can select visual forms that communicate business information accurately and efficiently.

• Visual encoding matches comparison tasks with position, length, colour and size
• IBCS conventions promote consistent notation, labelling, variance display and message titles
• Chart selection distinguishes trends, comparisons, composition, distribution and relationship questions
• Axis choices, baselines and scales prevent misleading apparent performance differences
• Colour palettes reserve emphasis for exceptions, alerts, selections and meaningful categories
• Data-ink reduction removes decoration, redundant labels, borders and unnecessary visual effects

Participants can design dashboard layouts and interactions around priority management questions.

• Dashboard wireframes place priority metrics, trends, exceptions and supporting detail deliberately
• Visual hierarchy directs attention through position, grouping, contrast and reading sequence
• Drill-through paths connect executive summaries with diagnosis-level operational detail
• Slicers and filters support controlled exploration without obscuring report interpretation
• Tooltips provide definitions, context, calculation notes and supporting detail on demand
• Mobile layouts adapt priority visuals, filters and navigation for smaller screens

Participants can test BI reports for accuracy, usability, performance and agreed business behaviour.

• Test cases verify data values, filters, calculations, formats and navigation paths
• Boundary testing examines first dates, last dates, zero values and missing records
• Reconciliation testing compares report outputs with approved source-system control totals
• User acceptance testing confirms decisions, terminology, workflow and usability expectations
• Performance testing checks load times, filter response and visual rendering behaviour
• Defect triage ranks faults by severity, business impact, workaround and release priority

Participants can define practical controls for report access, publication and change management.

• Role-based access restricts reports, data fields and actions by user responsibility
• Row-level security filters data according to authorised organisational or customer scope
• Workspace roles separate report development, approval, publication and administration duties
• Release checklists confirm data validation, approvals, documentation and access controls
• Change control records requested amendments, impact assessment, approval and deployment evidence
• Report retirement criteria identify obsolete outputs, replacement reports and archive requirements

Participants can plan reporting operations, ownership and improvement cycles after deployment.

• Reporting service models define request intake, prioritisation, support and escalation routes
• Refresh monitoring identifies failed loads, delayed data and incomplete reporting periods
• Usage metrics reveal unused reports, popular views, export behaviour and adoption patterns
• Feedback loops capture user questions, enhancement requests and recurring interpretation issues
• Data literacy guidance explains metric definitions, filters, limitations and appropriate use
• Quarterly report reviews assess continued value, quality issues and retirement candidates

Participants can design report analysis that moves from performance signals to plausible causes.

• Variance analysis separates actual, budget, forecast and prior-period performance differences
• Waterfall charts explain cumulative drivers behind favourable or adverse metric movements
• Pareto analysis ranks categories contributing most to defects, costs or delays
• Segmentation compares results by customer, product, location, channel and time
• Root cause questioning distinguishes observed patterns from validated causal explanations
• Exception thresholds trigger investigation based on materiality, risk and business tolerance

Participants can present report findings with clear messages, evidence and recommended actions.

• Message titles state the management conclusion rather than merely naming visuals
• Insight statements connect observed evidence, business implication and recommended action
• Narrative sequences move from headline performance through drivers to decision options
• Confidence statements identify data limitations, assumptions, timing gaps and unresolved questions
• Executive briefings distinguish urgent exceptions from monitored trends and routine performance
• Recommendation logs assign actions, owners, due dates and follow-up reporting measures

Participants can build, review and present a complete decision-ready BI reporting solution from requirements through governance.

• Reporting charter defines stakeholders, decisions, scope, success measures and operating assumptions
• KPI catalogue specifies calculations, targets, dimensions, exclusions and metric owners
• Dimensional model maps source data into facts, dimensions and report relationships
• Power BI report presents validated measures, interactions, exceptions and supporting detail
• Test evidence records reconciliation results, acceptance findings, defects and corrective actions
• Governance plan assigns access, refresh, change control, ownership and review responsibilities