Evaluate Current State22% of the exam
Data readiness checks for business requirements
Decide whether a customer's existing data can answer the business question: grain that cannot be recovered, measures a related table cannot split, unmatched rows and nulls, multi-fact models without a shared date table, snapshot freshness, report-style Excel files and location fields Tableau cannot geocode.
Evaluate whether existing data supports business needs.
~8 min read · 10 practice questions ·
What the exam expects
- Judge whether the grain of the delivered data can answer the requirement, and ask for more detail when it cannot.
- Explain replicated measures, deduplicated totals and inflated joined totals, and tell a modeling fault from a data gap.
- Diagnose missing dimension members and unexpected Null members in a related data source.
- Recognize when a multi-fact model lacks a shared table, such as a date table, for the requirement.
- Treat freshness as a fitness criterion: an extract is a snapshot until it is refreshed.
- Make report-style Excel files and location fields usable, or name the source fix.
Key terms:
- Grain: the level of detail of one row of a table.
- Replication: Tableau repeating a measure across a dimension that cannot split it.
- Unmatched value: a row in one related table with no matching row in the other.
- Base table / shared table: a multi-fact tree's root, and a table belonging to more than one tree.
- Custom geocoding: importing latitude and longitude for locations Tableau does not recognize.
Key facts
Preferred grain
- Detail
- As granular as possible, such as daily rather than monthly averages
Measure that can't be split
- Detail
- Replicated across the dimension
Dimension-only view of related tables
- Detail
- Uses inner joins
Show Empty Rows/Columns side effect
- Detail
- Densifies Date and Numeric Bin fields
Unrelated fields in a multi-fact viz
- Detail
- Dimensions cross joined; measures table scoped and repeated
Extract
- Detail
- A compressed snapshot of data
Blank rows, missing headers
- Detail
- Must be fixed in the Excel data
Data Interpreter
- Detail
- Does not change the underlying data
Custom geocoding file
- Detail
- .csv with Latitude and Longitude columns
Sources for this section (6)
- Data tipshelp.tableau.com (opens in a new tab)
- Relationships analysishelp.tableau.com (opens in a new tab)
- Multi-fact modelshelp.tableau.com (opens in a new tab)
- Use extractshelp.tableau.com (opens in a new tab)
- Data Interpreterhelp.tableau.com (opens in a new tab)
- Custom geocodinghelp.tableau.com (opens in a new tab)
- Why can Show Empty Rows be an unwanted fix for missing members?
- When does an unexpected Null member point to a modeling fault rather than to the data?
- What does Data Interpreter change in the original spreadsheet?
The questions are free to read. Answers with their sources and self-grading are included with the pack.
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