Simulado Tableau Desktop Specialist

A data source filter applies to the entire data source across all worksheets and is pushed to the database, limiting the rows retrieved — exactly the requirement here. A context filter only narrows data for the dependent filters on a single worksheet and must be set per sheet, so it does not provide a source-wide, all-sheets restriction. Creating an extract addresses storage and performance differently but, by itself, does not filter to Status = 'Active'; you would still need a filter (extract filter or data source filter) to limit the rows. Adding a dimension filter to each worksheet's shelf is both error-prone and sheet-specific — it does not guarantee the restriction everywhere and operates after data is already at the worksheet level rather than restricting what is retrieved for the whole source.

Bins are the dedicated feature for converting a continuous numeric field into equal-width intervals; specifying a bin size of 5 yields the 0-4, 5-9, 10-14 buckets requested, so it is correct. 'Create a group' is wrong because groups merge specific selected members of a dimension into named combinations and do not generate evenly spaced numeric ranges automatically; you would have to hand-pick values. 'Create a set' is wrong because a set divides members into just two states (in or out) based on a condition, not into multiple equal-width numeric bands. 'Create a string parameter listing the ranges' is wrong because a parameter only stores a single chosen value and does no bucketing on its own; it cannot assign each Quantity to a band without an additional calculation, and even then it would not be the purpose-built bucketing tool.

Data blending is correct because blending is specifically designed to combine data from two separate, independent data sources (here Snowflake and Google Sheets) by matching on a common linking field like Region, aggregating the secondary source to the level of the primary. An inner join in the physical layer is a misconception; joins require the tables to be part of the same connection/source, and you cannot physically join a Snowflake table to a Google Sheet in the physical layer. A relationship also operates within a single data source's logical layer and cannot span two entirely different connections. Pivoting the Google Sheets data only reshapes one source; it does nothing to combine the two sources, so combination is still required.