Transport KPI Dashboards with Power BI Training Course

Participants can assess and prepare transport data for dependable KPI reporting.

• Transport-management-system extracts profiled for keys, dates, measures and anomalies
• Shipment, consignment, stop, order and invoice grains separated correctly
• Data-quality rules detect duplicates, missing PODs and impossible transit times
• Power Query data types, locale settings and error handling applied
• Reference tables standardise carrier, lane, depot and customer classifications
• Source-to-dashboard lineage documented for auditable transport KPI reporting

Participants can build a star-schema model that supports transport analysis at multiple levels.

• Star schemas built around shipment facts and conformed transport dimensions
• Fact table grain selected before creating relationships or DAX measures
• Date dimensions support dispatch, collection, delivery and invoice analysis
• Active and inactive relationships handle planned and actual milestone dates
• One-to-many cardinality and filter direction diagnosed in transport models
• Dimensional attributes organised for carrier, lane, vehicle and service analysis
• Model views annotated to explain tables, keys and business definitions

Participants can create repeatable Power Query transformations for transport reporting datasets.

• Folder, database and spreadsheet connections selected for refreshable transport datasets
• Query steps clean carrier files without manual spreadsheet rework
• Merge and append operations combine shipment, cost and milestone records
• Parameters manage reporting periods, source locations and development environments
• Custom columns derive transit bands, late flags and lane identifiers
• Query folding considered when connecting to SQL transport data

Participants can write and validate DAX measures for core transport performance indicators.

• Measures calculate shipments, distance, cost, weight and utilisation consistently
• CALCULATE and filter context produce route, carrier and period comparisons
• DIVIDE prevents invalid percentage results in sparse operational data
• Time-intelligence measures compare current performance against prior periods
• On-time delivery measures apply agreed tolerance windows and exclusions
• Weighted averages avoid misleading service results across unequal shipment volumes
• Variance measures separate budget, contracted rate and actual freight cost

Participants can calculate and interpret transport KPIs for service, cost, capacity and quality.

• On-time-in-full calculated using promised dates, quantities and exception codes
• Transit-time performance segmented by lane, carrier, mode and customer
• Freight cost per shipment, kilogram and kilometre interpreted appropriately
• Accessorial cost analysis isolates detention, demurrage, fuel and waiting charges
• Vehicle fill, cube utilisation and empty kilometres reveal capacity losses
• Claims, damages and proof-of-delivery compliance tracked through service measures
• Targets and thresholds distinguish tolerable variation from operational intervention

Participants can design dashboard pages that support management review and operational follow-up.

• Visual selection matches monitoring questions, comparison tasks and decision cadence
• Executive pages combine outcome metrics, trends and material exceptions
• Operational pages expose late shipments, at-risk loads and carrier failures
• Drillthrough paths connect network summaries to shipment-level root causes
• Tooltips and report-page filters provide context without overcrowding visuals
• Conditional formatting highlights threshold breaches while retaining numeric evidence
• Accessible colours, labels and layouts support readable transport reporting

Participants can use Power BI visuals to identify geographic patterns, outliers and performance drivers.

• Map visuals reveal lane concentration, regional delays and depot performance
• Geographic fields prepared with categories, coordinates and data-quality checks
• Route analysis separates origin, destination and intermediate-stop reporting needs
• Scatter charts identify carrier cost-service trade-offs and outliers
• Decomposition trees investigate late delivery patterns through controlled dimensions
• Small multiples compare trend patterns across modes, regions and carriers

Participants can publish transport reports with appropriate controls for refresh, access and change management.

• Workspace roles control report development, publication and stakeholder access
• Scheduled refreshes planned around TMS extracts and operational reporting cycles
• Row-level security restricts customer, region and carrier views appropriately
• Certified semantic models reduce conflicting KPI definitions across reports
• Dashboard release checklists test filters, totals, drillthrough and refresh status
• Usage metrics identify abandoned pages and frequently investigated exceptions
• Change logs preserve KPI definitions, calculation decisions and ownership

Participants can connect dashboard findings to corrective action and plan a controlled first release.

• Exception-management routines connect dashboard signals to named corrective actions
• Carrier review packs combine service, cost, claims and capacity evidence
• Root-cause analysis uses Pareto charts, five whys and lane segmentation
• Weekly operating reviews distinguish data defects from genuine performance failures
• Dashboard backlog prioritises measures, visuals and data improvements by value
• Personal application plans define first dashboard releases and stakeholder reviews