Plan and Prepare Data Connections22% of the exam
Minimum granularity for data source design
Find the coarsest grain that still answers every requirement, and know what pre-aggregation destroys: finer date levels, averages over the original rows, distinct counts, medians, security attributes and incremental refresh.
Specify the requirements for minimum level of granularity.
~7 min read · 7 practice questions ·
What the exam expects
- Derive the minimum grain of a data source from a set of requirements, keeping every dimension that can't be derived from another.
- Predict which questions a summarized table or aggregated extract can no longer answer.
- Keep the attributes row-level security filters on when the data is summarized.
- Deduplicate a snapshot table to one row per entity in Tableau Prep.
- Keep a small extract refreshing incrementally by summarizing upstream instead of in the extract.
Key terms:
- Grain: what one row represents, such as one order line or one store per day.
- Minimum grain: the coarsest grain from which every requirement can still be aggregated.
- Non-additive aggregate: an aggregation whose results can't be aggregated again along a dimension, such as COUNTD or MEDIAN.
- Roll-up: storing dates at a coarser level, such as Month, in an aggregated extract.
- Entitlement: a combination of attributes the data can be filtered on for security.
Key facts
Recommended data shape
- Detail
- As granular as possible rather than aggregated
Non-additive aggregates
- Detail
- COUNTD, MEDIAN, RAWSQLAGG: calculated individually, not re-aggregated
Aggregate data for visible dimensions
- Detail
- Measures use their default aggregation; dates can roll up to Year, Month and so on
Hidden fields
- Detail
- Excluded from the extract
Incremental refresh
- Detail
- Unavailable with Aggregation; requires All Rows
Dynamic user filter
- Detail
- Data must include the security information
Prep rank default order
- Detail
- Descending; add ASC to change
ROW_NUMBER
- Detail
- No skipped values; not in the visual calculation editor
Sources for this section (6)
- Data tipshelp.tableau.com (opens in a new tab)
- Troubleshoot Data Blendinghelp.tableau.com (opens in a new tab)
- Extract Your Datahelp.tableau.com (opens in a new tab)
- Refresh Extractshelp.tableau.com (opens in a new tab)
- RLS optionshelp.tableau.com (opens in a new tab)
- Prep calculationshelp.tableau.com (opens in a new tab)
- When can a ROW_NUMBER deduplication return a different surviving row on each flow run?
- Why does AVG over a summarized table differ from the average of the original events?
- Which RANK variant gives tied rows the rank of the last instance of the value?
The questions are free to read. Answers with their sources and self-grading are included with the pack.
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