Tableau Data Analyst study plan

Build a Tableau workbook connected to at least two different source types (a file and a database or published data source)

Create and document join, union, and relationship configurations on sample tables, noting how each changes row counts

Classify five sample fields by data type and geographic role, then correct any misassignments

Write three calculated fields using string and date functions and verify outputs against source rows

Clean a messy dataset by splitting, pivoting, and fixing data-type inconsistencies

Build a reusable data source with renamed fields, folders, and default number/date formats

Extract a subset of data and compare extract performance and filters against the live connection

Resolve at least three data quality issues (nulls, duplicates, outliers) and record the rule applied to each

Choose the correct chart type for five analytical questions and justify each choice in writing

Build a view using at least two dimensions and two measures with proper aggregation and disaggregation

Create calculated fields using LOD expressions and confirm results against manually computed values

Apply filters at dimension, measure, and table-calc levels and explain the order of operations

Construct reference lines, bands, and distributions to highlight thresholds in three views

Build a small-multiples or trellis view and tune it for readability

Audit a prior data source for aggregation mismatches and correct at least two

Write three table calculations (rank, percent of total, running sum) and verify each

Assemble a dashboard using containers and layout hierarchy rather than floating objects

Add at least three interactive actions (filter, highlight, parameter) and test each across sheets

Design a consistent color, font, and number-format scheme and apply it across all sheets

Add a title, subtitle, and tooltip set that explains the dashboard's purpose without external notes

Build a two-to-three-point story that walks a viewer from problem to conclusion

Refine dashboard performance by reducing marks, removing unused fields, and simplifying extracts

Test the dashboard at two device layouts and fix overflow or unreadable elements

Run a five-person usability check and log at least three concrete improvements

Configure permissions for a project and a published data source, then verify access with a second account

Set up a scheduled extract refresh and confirm it runs successfully

Apply row-level security using a user filter and test it against two user roles

Document data source lineage and ownership for one published source

Review all four domains and list remaining weak spots with a fix for each

Complete two timed practice sets mixing calculation, dashboard, and governance questions

Revisit incorrect items and write the reasoning for the correct approach

Finalize a portfolio page linking your dashboard, story, and governance documentation