Analytics-DA-201 Exam Information and Outline
Salesforce Certified Tableau Data Analyst
Analytics-DA-201 Exam Syllabus & Study Guide
Before you start practicing with our exam simulator, it is essential to understand the official Analytics-DA-201 exam objectives. This course outline serves as your roadmap, breaking down exactly which technical domains and skills will be tested. By reviewing the syllabus, you can identify your strengths and focus your study time on the areas where you need the most improvement.
The information below reflects the latest 2026 course contents as defined by Tableau. We provide this detailed breakdown to help you align your preparation with the actual exam format, ensuring there are no surprises on test day. Use this outline as a checklist to track your progress as you move through our practice question banks.
Below are complete topics detail with latest syllabus and course outline, that will help you good knowledge about exam objectives and topics that you have to prepare. These contents are covered in questions and answers pool of exam.
Connect to and Transform Data
- Connect to data sources including files (Excel, CSV, PDF, spatial), databases (SQL Server, PostgreSQL, etc.), cloud sources (Google Sheets, Snowflake, etc.), and published data sources on Tableau Server/Cloud.
- Use live connections vs. extracts (when to use each, performance implications).
- Perform joins (inner, left, right, full, cross-database), unions, and relationships (logical vs. physical layers in Tableau's data model).
- Pivot, split, group, alias, and clean data in Tableau Desktop.
- Use Tableau Prep Builder for advanced data flows: clean steps, aggregate, join, union, pivot, filter, calculate fields, input/output steps.
- Handle data quality issues: nulls, duplicates, inconsistent formats, data roles (e.g., geographic, currency).
- Blend data from multiple sources when relationships aren't feasible.
- Create and manage metadata (rename fields, set data types, add descriptions, hide unused fields).
Explore and Analyze Data
- Build basic and advanced calculations: string, date, numeric, conditional (IF/CASE), type conversions.
- Create Level of Detail (LOD) expressions: FIXED, INCLUDE, EXCLUDE (common scenarios like cohort analysis, percent of total, customer-level calcs ignoring filters).
- Use table calculations: running total, percent of total, rank, moving average, YTD, difference from, percent difference.
- Apply parameters for dynamic control (what-if analysis, top N, dynamic measures/dimensions).
- Use sets (combined, conditional, IN/OUT) and groups for segmentation.
- Perform trend analysis: trend lines, forecasting (add forecast, customize model), clustering.
- Use analytics pane features: reference lines/bands/distributions, box plots, totals/subtotals.
- Interpret and create statistical insights: averages, medians, correlations, outliers.
- Create calculated fields for ad-hoc analysis (e.g., cohort flags, YoY growth).
- Use quick table calculations and edit them for custom behavior.
- Handle hierarchical data and drill-downs effectively.
Create Content
- Design effective visualizations: bar charts, line charts, maps, scatter plots, heatmaps, treemaps, bullet charts, etc.
- Choose appropriate chart types based on data and questions (show distribution, comparison, relationship, composition).
- Build interactive dashboards: filter actions, highlight actions, URL actions, parameter actions.
- Use dashboard objects: layout containers (horizontal/vertical), blank objects, images, web page objects, navigation buttons.
- Apply formatting best practices: color palettes (accessible, branded), fonts, tooltips (rich + viz in tooltip), labels, axes.
- Create device-specific layouts (phone, tablet, desktop) for responsive design.
- Build stories to present narrative insights with guided flow.
- Optimize performance in views/dashboards (extract filters, reduce marks, aggregate data).
- Add interactivity: show/hide containers, sheet swapping via parameters.
- Ensure accessibility (color contrast, alt text where applicable, logical tab order).
Publish and Manage Content on Tableau Server and Tableau Cloud
- Publish data sources (live vs. embedded extract) and workbooks to Server/Cloud.
- Schedule extract refreshes and manage refresh schedules/failures.
- Set permissions: project-level, content-level (view, interact, download, publish, manage).
- Use subscriptions and data-driven alerts for stakeholders.
- Certify data sources and manage lineage/impact analysis.
- Embed credentials securely or use OAuth where supported.
- Understand governance features: collections, favorites, tags, metadata management.
- Troubleshoot common publish issues (e.g., data source not found, permissions errors).
- Differentiate between Tableau Server and Tableau Cloud features (e.g., Cloud auto-scaling, activity logs).