Free Analytics-Con-301 sample questions

Correct answer: Create a published Extract with an Incremental Refresh schedule set to run daily after the warehouse update.

For large datasets (500M rows) where data is static throughout the day, an Extract offers superior query performance compared to a Live connection. Since the data only changes once every 24 hours, an Incremental Refresh scheduled after the warehouse load ensures data currency without the overhead of querying the live database for every user interaction.

Correct answer: Tableau will keep the tables separate and perform context-aware aggregations at runtime, preventing measure duplication.

Relationships (the 'noodle' connections in the Logical Layer) differ from physical joins. They do not merge tables into a single flat table immediately. Instead, Tableau queries them independently at the appropriate level of detail during analysis, ensuring that measures from the 'Targets' table (monthly) are not duplicated for every row in the 'Sales' table (transactional).

Correct answer: Change the 'Region' filter to a Context Filter.

In Tableau's Order of Operations, Dimension Filters are applied *after* Top N filters. This means the Top 10 are calculated on the entire dataset first, and then the Region filter hides rows. By adding the Region filter to Context, it moves up the pipeline (before Top N), ensuring the Top 10 are calculated *within* the filtered subset. flowchart TD A[Extract Filters] --> B[Data Source Filters] B --> C[Context Filters] C --> D[Fixed LODs] D --> E[Top N Filters] E --> F[Dimension Filters] style C fill:#f9f,stroke:#333,stroke-width:2px style E fill:#bbf,stroke:#333,stroke-width:2px

Correct answers: Implementing Row-Level Security (RLS) using a join to an entitlement table that results in row duplication (Row Multiplication).; Using a specific join type (like Full Outer Join) that is not supported by the Relationship heuristics for the given data source.

RLS often relies on 'exploding' rows when a user has multiple roles or entitlements (Row Multiplication), which is a behavior of physical joins. Relationships attempt to preserve the native level of detail and avoid duplication, which can break RLS models dependent on row multiplication.

While Relationships support most join logic, specific requirements for a forced Full Outer Join or specific join clauses often require dropping into the Physical Layer.

Correct answer: AVG({FIXED [Customer Name] : SUM([Sales])})

This expression first calculates the total sales for each customer (inner aggregation) regardless of the view level, and then the outer aggregation (AVG) averages those customer totals based on the dimensions in the view (Region).

Correct answer: False

False. Tableau Prep (and Desktop) Wildcard Union is permissive. If columns do not match, it will union the matching columns and create nulls for the mismatched columns in the respective rows. It does not fail immediately; it creates a superset of all columns.