Salesforce Tableau Data Analyst study plan

Connect to at least three source types (flat file, spreadsheet, and a database table) and assign the correct data type to every field.

Combine tables with one join, one relationship, and one union, and write one sentence per method stating what granularity it preserves.

Apply Data Interpreter, a pivot, and a split to clean a single messy file, logging each transformation and the row count before and after.

Reconcile the cleaned source against the raw file with an aggregation check that proves no rows were duplicated or dropped.

Write 12 calculated fields spanning string, date, and logical functions, including two that explicitly handle nulls.

Build one FIXED, one INCLUDE, and one EXCLUDE level-of-detail expression, each answering a stated business question.

Prove the filter order of operations by building one sheet that shows extract, data source, context, dimension, and measure filters acting in sequence.

Create one parameter-driven calculation and one set-based calculation and document when each is preferable.

Sort, group, and bin one measure to answer three distribution questions.

Build three table calculations (running total, percent of total, rank) and set the compute-using direction correctly for each.

Add a trend line, a forecast, and a reference line to relevant views and interpret each in two sentences.

Compare four chart types against the same question and justify the one you keep.

Build a bar, a line, a scatter plot, a highlight table, and a dual-axis combination chart from the same data source.

Assemble a dashboard of four or more worksheets using layout containers and a fixed dashboard size.

Add three dashboard actions (filter, highlight, and URL) and confirm each fires as intended.

Apply consistent number formats, axis titles, and a colorblind-safe palette across every view.

Create separate device layouts for desktop, tablet, and phone.

Record and review performance, then reduce mark count and remove unused fields until every view renders in under three seconds.

Add parameter-driven and set-driven interactivity so a viewer can switch the measure and filter by segment without editing the workbook.

Add dashboard navigation, informative tooltips, and dynamic zone visibility.

Publish a workbook to a server or cloud site and set project permissions for three distinct group types.

Configure a scheduled extract refresh and write a short comparison of live versus extract trade-offs for this data.

Implement row-level security with a user filter and verify it by logging visible row counts for two test users.

Create a subscription and a data-driven alert and confirm both deliver.

Organize content into projects and apply a naming and tagging convention across all published items.

Certify one data source and state the governance criteria it had to meet.

Document handling for refresh failures and version history recovery.

Write a content lifecycle from draft through review, certification, and retirement.

Complete a timed mixed-domain practice run and list your five weakest objectives by score.

Rebuild two weak-topic deliverables from a blank workbook without notes.

Write three short teach-back explanations: level-of-detail versus table calculations, extract versus live connection, and row-level security design.

Re-test only the missed objectives until each reaches at least 80 percent.