Tableau Business Intelligence Training Course

Participants can connect, prepare and validate data for Tableau analysis.

• Live connections and extracts selected against freshness, scale and access requirements
• Files, relational databases and published sources connected through Tableau connectors
• Tableau Prep Builder cleans fields, splits values and standardises categories
• Pivoting, unions and field renaming reshape operational files for analysis
• Data Interpreter handles irregular spreadsheet headers, notes and merged cells
• Null values, duplicates and invalid dates assessed using profiling views
• Extract refresh settings documented with source ownership and failure escalation

Participants can create Tableau data models that preserve correct business logic.

• Relationships preserve separate table grain until fields are queried together
• Physical joins selected using join clauses and expected record retention
• Unioned monthly files aligned through consistent schemas and field definitions
• Referential integrity checks expose unmatched keys and duplicate business entities
• Star-schema concepts distinguish fact tables, dimensions and conformed dimensions
• Row-level validation reconciles Tableau totals against approved source reports
• Data-quality rules recorded for missing values, outliers and late-arriving records

Participants can create reliable Tableau calculations for common business metrics.

• Calculated fields apply arithmetic, conditional logic, date functions and string functions
• Aggregation rules distinguish SUM, AVG, COUNTD and non-additive business measures
• Parameters support scenario assumptions, metric selection and user-controlled thresholds
• FIXED level of detail expressions calculate stable customer and period metrics
• INCLUDE and EXCLUDE expressions alter dimensionality within worksheet calculations
• Table calculations compute running totals, moving averages and period comparisons
• Order of operations explains interactions among filters, LOD expressions and calculations

Participants can select and format Tableau views that communicate analytical findings accurately.

• Analytical questions classified as comparison, distribution, composition, relationship or trend
• Bar charts compare ranked categories using sorted values and zero baselines
• Line charts show time-series patterns with appropriate date granularity
• Scatter plots test relationships, outliers and segment-level performance differences
• Reference lines, bands and distributions provide targets and statistical context
• Colour, position, size and labels applied using perceptual accuracy principles
• Accessibility checks assess contrast, colour dependence, labels and explanatory text

Participants can build interactive dashboards that support focused user decisions.

• Dashboard wireframes define audience tasks, primary metrics and information hierarchy
• Tiled and floating containers control alignment, spacing and responsive layout
• Quick filters, parameter controls and context filters manage user exploration
• Filter actions, highlight actions and URL actions connect related analytical views
• Viz in Tooltip adds detail without overcrowding the primary dashboard
• Device Designer creates layouts for desktop, tablet and mobile viewing
• Dashboard titles, annotations and captions document interpretation and source context

Participants can apply Tableau mapping and analytical features to investigate patterns.

• Geographic roles assign locations, administrative areas and postal-code fields correctly
• Symbol maps and filled maps selected according to geographic data type
• Custom geocoding resolves organisational territories and nonstandard location identifiers
• Dual-axis maps combine rates, volumes and geographic reference information
• Trend lines assess linear relationships and explain model assumptions visually
• Forecasting uses exponential smoothing with seasonality and prediction intervals
• Clustering groups records using selected measures and interpretable segment labels

Participants can publish Tableau content with appropriate access and governance controls.

• Tableau Cloud and Tableau Server roles determine authoring and viewing permissions
• Projects, workbooks and data sources organised through agreed content structures
• Certified data sources signal approved fields, definitions and accountable owners
• Row-level security restricts records using user filters and entitlement tables
• Permissions tested for workbook access, downloads, subscriptions and data visibility
• Refresh schedules, extract failures and subscriptions monitored through administrative views
• Data-source documentation records lineage, refresh frequency, owners and permitted use

Participants can diagnose slow Tableau workbooks and apply quality-assurance controls.

• Performance Recording identifies slow queries, layout rendering and calculation bottlenecks
• Extracts, aggregation and data-source filters reduce unnecessary query workload
• Context filters used selectively when dependent filters require performance improvement
• Workbook design limits mark counts, excessive sheets and redundant quick filters
• Calculation review removes repeated logic and expensive string-level operations
• Dashboard QA checks metric accuracy, interactions, accessibility and device layouts
• Release checklists confirm owners, permissions, refreshes and stakeholder sign-off

Participants can plan a controlled Tableau dashboard delivery for a business reporting need.

• Dashboard requirements translated into user stories, acceptance criteria and metric definitions
• Source-system owners, data stewards and report consumers assigned accountable responsibilities
• Publication decisions compare sandbox, test and production Tableau environments
• Change-control requests assess calculation impact, audience need and maintenance cost
• Usage metrics identify unused content, popular views and adoption barriers
• Stakeholder feedback converted into prioritised dashboard improvement actions
• Personal application plans identify a reporting process for immediate redesign