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Salesforce Tableau Data Analyst study materials
Salesforce Tableau Data Analyst study resources

Salesforce Tableau Data Analyst practice questions

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Question 1Data Preparation

A team needs dashboards that reflect new transactions the instant they are committed to the source database, with no scheduled rebuild. Which connection type should the analyst choose?

  1. Pivot
  2. Live connection Correct answer.
  3. Union
  4. Extract

Explanation

A live connection sends queries to the underlying data source each time a view is rendered, so committed changes appear without a refresh step. Extracts copy data into Tableau storage and only update on refresh.

Question 2Data Preparation

Which file format does Tableau use to store a data extract?

  1. .tds
  2. .hyper Correct answer.
  3. .csv
  4. .twbx

Explanation

Extracts are saved in the .hyper format, a compressed columnar file designed for fast in-memory queries. The other extensions denote a packaged workbook, a data source definition, and a plain text file.

Question 3Data Preparation

Which feature appends rows from two tables that have the same structure into a single longer table?

  1. Union Correct answer.
  2. Blend
  3. Join
  4. Relationship

Explanation

A union stacks tables vertically, producing more rows and keeping the same set of columns. Joins add columns by matching keys, relationships link logical tables, and blends combine sources at the worksheet level.

Question 4Data Preparation

An analyst receives a spreadsheet where each month is a separate column and needs a tall table with one row per month. Which feature performs this reshaping?

  1. Pivot Correct answer.
  2. Join
  3. Split
  4. Union

Explanation

Pivoting converts columns into rows, turning a wide crosstab into a narrow, normalized structure. Splitting works on delimiters inside a single field, while joins and unions act across tables.

Question 5Data Preparation

Which join type returns only the rows whose key values appear in both tables?

  1. Right join
  2. Full outer join
  3. Left join
  4. Inner join Correct answer.

Explanation

An inner join keeps only rows with matching key values on both sides of the join. Left, right, and full outer joins additionally keep unmatched rows from one or both tables.

Question 6Data Preparation

A field imported from a spreadsheet contains values such as 2023-01-15 and is currently treated as text. Which data type should be assigned so date functions work correctly?

  1. Date Correct answer.
  2. Integer
  3. String
  4. Boolean

Explanation

The date data type stores calendar dates and enables date-level functions such as DATETRUNC and DATEDIFF. As text, the values would sort and filter alphabetically rather than chronologically.

Question 7Data Preparation

A field contains combined values like "Doe, Jane" and the analyst needs separate last name and first name fields. Which feature should be used?

  1. Split Correct answer.
  2. Pivot
  3. Alias
  4. Group

Explanation

Split uses a delimiter or repeating pattern to break one field into multiple new fields. Grouping combines existing members, aliasing relabels members, and pivoting moves columns into rows.

Question 8Data Preparation

A numeric field is added to a data source for the first time. Which role does Tableau assign it by default?

  1. Parameter
  2. Measure Correct answer.
  3. Dimension
  4. Group

Explanation

Tableau assigns numeric fields to the Measure role by default and aggregates them when they are placed on a shelf. Non-numeric fields default to the Dimension role.

Question 9Data Preparation

An analyst connects to a very large transactional table but only needs the current year's rows and wants faster performance. Which approach best meets both needs?

  1. Join the table to itself on the order date
  2. Add a context filter to each worksheet
  3. Create an extract with a filter for the current year Correct answer.
  4. Create a live connection and filter the worksheet

Explanation

An extract filter limits the rows written into the extract, so only the needed year is stored locally and queries run against a much smaller data set. Worksheet-level filters do not reduce how much data a live connection must query.

Question 10Data Preparation

What does the Data Interpreter option do when enabled on a data source?

  1. It converts text fields into measures
  2. It joins tables that share a key field
  3. It cleans headers and footnotes from crosstabs Correct answer.
  4. It schedules automatic extract refreshes

Explanation

The Data Interpreter detects and removes extraneous titles, headers, footnotes, and merged cells so the actual table is read cleanly. It does not alter field roles, join tables, or manage refresh schedules.

Question 11Data Preparation

Which statement about tables connected by a relationship in the logical layer is correct?

  1. They are merged into one flattened table
  2. They stay separate and are joined at query time Correct answer.
  3. They work only with extracts, not live data
  4. They must have identically named key fields

Explanation

Relationships keep tables logically separate, and Tableau builds the appropriate join at query time based on the fields used in the view. Field names do not need to match, and relationships work with both live connections and extracts.

Question 12Data Preparation

Which function returns the number of distinct non-null values in a field?

  1. SUM
  2. AVG
  3. COUNT
  4. COUNTD Correct answer.

Explanation

COUNTD returns the count of unique, non-null values in a field, which is useful for counting customers or products without duplicates. COUNT returns the number of non-null rows rather than distinct values.

Question 13Data Preparation

A filter is added at the data source level rather than on an individual worksheet. What is the effect?

  1. It hides the filtered field from the Data pane
  2. It modifies the underlying database table
  3. It applies to every worksheet using that data source Correct answer.
  4. It applies only to the active worksheet

Explanation

A data source filter is stored with the data source, so every worksheet built from that source inherits the restriction. Worksheet filters, by contrast, affect only the sheet where they are created.

Question 14Data Preparation

An analyst needs to join tables that come from two separate database connections into a single table in the physical layer. Which capability makes this possible?

  1. Relationship
  2. Blend
  3. Cross-database join Correct answer.
  4. Union

Explanation

A cross-database join lets the physical layer combine tables from different connections into one joined table. Blending combines separate sources at the worksheet level instead of producing a single joined table.

Question 15Data Preparation

What is the difference between renaming a field and aliasing a dimension member?

  1. Renaming edits the source data; aliasing does not
  2. Both change only the worksheet title
  3. Aliasing changes the data type; renaming does not
  4. Renaming changes the field name; aliasing changes member labels Correct answer.

Explanation

Renaming changes how the field itself appears in the Data pane and on shelves. Aliasing replaces the displayed label for individual members, such as showing "East Region" in place of a code value.

Question 16Data Preparation

Which feature combines several members of a dimension into one category while leaving the source data unchanged?

  1. Parameter
  2. Bin
  3. Group Correct answer.
  4. Hierarchy

Explanation

A group lets you merge selected dimension members into a single category for analysis without altering the underlying records. Bins create numeric ranges, parameters hold constant input values, and hierarchies organize fields into drill paths.

Question 17Data Preparation

Which statement about the primary and secondary sources in a data blend is correct?

  1. The primary source sets the view's level of detail Correct answer.
  2. The secondary source sets the view's level of detail
  3. Both sources must come from the same connection
  4. Blends require identically named link fields

Explanation

In a blend, the primary source determines the granularity of the view, and values from the secondary source are aggregated up to that level before being matched. Link fields may have different names as long as the analyst defines the mapping.

Question 18Data Preparation

In a left join, a row in the left table has no matching row in the right table. What appears in the right table's columns for that row?

  1. Zeros
  2. The previous row's values
  3. Blank strings
  4. Nulls Correct answer.

Explanation

A left join keeps unmatched left rows and fills the right table's columns with nulls, since no record exists on that side. Zeros or blank strings would imply actual stored values.

Question 19Data Preparation

What happens when an analyst changes a field's data type on the data source page?

  1. Only the active worksheet is affected
  2. Rows with invalid values are deleted
  3. The database column is permanently converted
  4. Tableau reinterprets values for all sheets using the field Correct answer.

Explanation

A data type change is stored with the data source, so every worksheet that uses the field sees the new interpretation. The underlying database column is untouched and no rows are removed.

Question 20Data Preparation

Assuming all of these filters exist in a workbook, which one is evaluated first when a view is queried?

  1. Measure filter
  2. Extract filter Correct answer.
  3. Context filter
  4. Dimension filter

Explanation

Filters are applied in a fixed order: extract filters, then data source filters, then context filters, then dimension filters, and finally measure filters. Extract filters therefore run before any of the others listed.

Question 21Data Preparation

A relationship connects an Orders table to a Returns table. Which statement about the level of detail of a view built on this relationship is correct?

  1. It comes from the dimensions used in the view Correct answer.
  2. It is always the finest grain of any related table
  3. It always follows the left table in the relationship
  4. It is fixed by the first table added to the source

Explanation

With relationships, the grain of the query is determined by the dimensions placed in the view rather than by a predefined join result. This is what allows one data source to answer questions at different levels of detail.

Question 22Data Preparation

What is the effect of changing a relationship's cardinality setting from many-to-one to many-to-many?

  1. It forces an inner join at query time
  2. It duplicates rows in the secondary table
  3. It changes performance options but not the results Correct answer.
  4. It filters out rows without a match

Explanation

The cardinality setting in a relationship is informational: it tells Tableau what to expect so it can expose relevant performance options. It does not filter rows, force a join type, or duplicate records.

Question 23Data Preparation

Which statement accurately describes an incremental extract refresh?

  1. It removes rows deleted from the source table
  2. It refreshes only the extract's metadata
  3. It rebuilds the extract completely from scratch
  4. It adds new rows and updates changed rows but keeps deleted rows Correct answer.

Explanation

An incremental refresh appends rows that are new and updates rows that changed since the last refresh, based on a designated column. Rows deleted at the source are not removed, so a full refresh is needed to reconcile deletions.

Question 24Data Preparation

Which statement correctly distinguishes the logical layer from the physical layer?

  1. Relationships exist only in the physical layer
  2. Both layers store unions the same way
  3. Joins and unions are physical; relationships are logical Correct answer.
  4. Unions exist only in the logical layer

Explanation

The physical layer holds tables combined with joins and unions, producing one flattened structure per logical table. The logical layer holds relationships between those logical tables, keeping them separate until query time.

Question 25Data Preparation

Why can a join return more rows than either of its input tables?

  1. Unmatched rows are always duplicated
  2. Null keys are counted twice by Tableau
  3. One row matches several rows on the other side Correct answer.
  4. Each join condition adds an extra row

Explanation

When a key value repeats on both sides of a join, each combination of matching rows becomes a separate output row, which inflates row counts and can overstate aggregated measures. This is the classic many-to-many join effect.

Question 26Data Preparation

A text field contains country names such as France and Brazil. Which step lets Tableau plot these values on a map view?

  1. Add the field to a set and place the set on Detail.
  2. Assign the Country/Region geographic role to the field. Correct answer.
  3. Convert the field from a dimension to a measure.
  4. Change the field data type to Number (Whole).

Explanation

Assigning a geographic role tells Tableau that the values represent locations, so they can be geocoded and plotted on a map. Changing the data type or role does not supply any location meaning.

Question 27Data Preparation

Which transformation appends the rows of a second table beneath the rows of the first table to produce one longer table?

  1. A relationship between two logical tables.
  2. A blend of two data sources.
  3. A left join on a shared key.
  4. A union of the two tables. Correct answer.

Explanation

A union stacks the rows of multiple tables into a single table, increasing the row count while keeping the same columns. Joins, relationships and blends combine columns rather than appending rows.

Question 28Data Preparation

Tableau saves a data extract in which file format?

  1. .hyper Correct answer.
  2. .twbx
  3. .tfl
  4. .tds

Explanation

The .hyper format is Tableau's columnar extract engine and is what an extract file uses. The other extensions belong to data source files, packaged workbooks and prep flows.

Question 29Data Preparation

Which function returns a Boolean value that indicates whether an expression is null?

  1. ATTR
  2. IFNULL
  3. ISNULL Correct answer.
  4. ZN

Explanation

ISNULL evaluates an expression and returns True or False depending on whether the value is null. The other functions return replacement values or a single representative value.

Question 30Data Preparation

A column contains US ZIP codes such as 02134 and 90210. Which data type preserves the leading zero?

  1. String Correct answer.
  2. Boolean
  3. Number (Whole)
  4. Number (Decimal)

Explanation

Text values keep every character as stored, so the leading zero survives. Numeric types interpret the value as a number and discard the leading zero.

Question 31Data Preparation

Which feature divides a continuous measure into a series of equal-sized numeric ranges?

  1. Bins Correct answer.
  2. Sets
  3. Groups
  4. Hierarchies

Explanation

Bins split a continuous measure into equally sized intervals so that the measure can be used like a dimension. Groups, sets and hierarchies operate on discrete members or field organization.

Question 32Data Preparation

Which join type returns only the rows that have matching key values in both tables?

  1. Left join
  2. Full outer join
  3. Right join
  4. Inner join Correct answer.

Explanation

An inner join keeps only the rows whose keys are present on both sides of the join. Outer joins additionally preserve unmatched rows from one or both tables.

Question 33Data Preparation

A crosstab has separate columns for Jan, Feb and Mar. Which transformation restructures it so month names appear as values in a single field?

  1. Aggregate
  2. Union
  3. Split
  4. Pivot Correct answer.

Explanation

Pivoting converts wide columns into a field-name column and a value column, turning months into rows. The other options divide text, append tables or summarize rows.

Question 34Data Preparation

A union is built from a wildcard pattern that matches files in a folder. A new matching file is added and the data source is refreshed. What happens?

  1. The new file is ignored until the union is edited by hand.
  2. The new file's rows are included after the refresh. Correct answer.
  3. The new file is added only if its column names differ.
  4. The new file replaces the first table in the union.

Explanation

A wildcard union re-evaluates the matching files each time the data source is refreshed, so newly added files that fit the pattern contribute rows automatically. Manual editing is not required.

Question 35Data Preparation

An Orders table stores Order ID as a whole number, and a Returns table stores Order ID as text. The analyst joins the two fields. What is the most likely outcome?

  1. The join returns no matching rows because the key types differ. Correct answer.
  2. Tableau blends the two data types and matches every row correctly.
  3. The join returns every row of both tables as a cross join.
  4. Tableau converts the text column to numbers and matches every row.

Explanation

Join keys must be of compatible data types; comparing a numeric key to a text key does not produce matches. Making both keys the same type is required before the join behaves as expected.

Question 36Data Preparation

An analyst renames a field that is already used on several worksheets. Which command keeps those worksheets working with the new name?

  1. Hide
  2. Duplicate
  3. Replace References Correct answer.
  4. Alias

Explanation

Replace References updates every place the old field name appears, including worksheets and calculations, so nothing breaks. Without it, renamed fields can leave stale references behind.

Question 37Data Preparation

A calculated field is created on the Data Source page rather than on a worksheet. What is the result?

  1. It must be recreated on each worksheet that needs it.
  2. It is added to the data source and available on all sheets using it. Correct answer.
  3. It is added only to the sheet that was active when it was created.
  4. It is stored but cannot be used until the workbook is refreshed.

Explanation

A calculation created on the Data Source page is saved as part of the data source, so every worksheet built on that source can use it. Worksheet-level calculations are scoped differently.

Question 38Data Preparation

Which object defines a reusable custom combination of dimension members that supports IN/OUT membership?

  1. A bin
  2. A hierarchy
  3. A set Correct answer.
  4. A group

Explanation

A set stores a defined list of dimension members and can be used as an IN/OUT predicate in calculations and filters. Groups, bins and hierarchies do not offer membership testing.

Question 39Data Preparation

A CSV file displays accented characters as symbols after connecting. Which setting should the analyst adjust?

  1. The workbook's default number format
  2. The field's geographic role
  3. The text file's character set Correct answer.
  4. The extract's sampling method

Explanation

Text File Properties stores the character set used to decode the file; when it does not match the file's encoding, accented characters render as symbols. Changing roles, formats or sampling does not affect decoding.

Question 40Data Preparation

An analyst drags a Country dimension onto a Region dimension in the Data pane and drops it. What is created?

  1. A hierarchy Correct answer.
  2. A set
  3. A group
  4. A combined field

Explanation

Dropping one field onto another in the Data pane builds a hierarchy, placing the dragged field beneath the target field as a lower level. This supports drill-down without changing the underlying data.

Question 41Data Preparation

What is the effect of hiding a field in the Data pane?

  1. The field is hidden from the Data pane but remains in the data source. Correct answer.
  2. The field is removed from the data source and its values are discarded.
  3. The field's values are excluded from every view in the workbook.
  4. The field is renamed to a system-generated name.

Explanation

Hiding only affects the Data pane display; the field still exists in the data source and can be shown again. Removing a field is a separate action from hiding it.

Question 42Data Preparation

Which file extension identifies a packaged data source that includes its underlying local files?

  1. .hyper
  2. .twbx
  3. .tdsx Correct answer.
  4. .tds

Explanation

.tdsx packages a data source together with files such as extracts so it can be shared on another machine. A .tds holds only connection and metadata information.

Question 43Data Preparation

Two tables are added to the physical layer with no join clause defined between them. What happens to the data?

  1. The tables are blended on the first field with a matching name.
  2. Only the first table is used until a join is defined.
  3. The tables are combined as a cross join, multiplying rows. Correct answer.
  4. Tableau prompts for a relationship key before loading rows.

Explanation

Without a join clause the physical layer pairs every row of one table with every row of the other, producing a cross join and a much larger row count. A relationship or join condition must be defined to avoid this.

Question 44Data Preparation

What role does Tableau assign to a date field when it is first added to a data source?

  1. Dimension Correct answer.
  2. Neither dimension nor measure until it is used
  3. Continuous measure
  4. Measure

Explanation

Tableau assigns the dimension role to date fields by default because dates are typically used to group and filter data. Numeric fields, by contrast, default to the measure role.

Question 45Data Preparation

Which extract option reduces the size of an extract by excluding fields that no worksheet uses?

  1. Incremental refresh
  2. Aggregate the data
  3. Hide unused fields Correct answer.
  4. Add a data source filter

Explanation

The hide unused fields option drops fields that are not referenced anywhere in the workbook, removing columns from the extract. The other options change which rows are stored or how the extract refreshes.

Question 46Data Preparation

A 10-row table and a 5-row table share a key field, but no key values match. How many rows does a full outer join return?

  1. 15 Correct answer.
  2. 5
  3. 0
  4. 10

Explanation

A full outer join keeps unmatched rows from both sides, so all 10 left rows and all 5 right rows appear with nulls opposite them, giving 15 rows. Inner and single-sided outer joins return fewer rows.

Question 47Data Preparation

A crosstab has one row per customer and twelve columns for months. After pivoting those twelve columns into a single field, how many rows does each original customer produce?

  1. Twelve rows Correct answer.
  2. Two rows
  3. One row containing twelve fields
  4. One row, with the months concatenated

Explanation

Pivoting converts each column into a row, so twelve month columns generate twelve rows per original record, each holding one month and its value. The total row count grows by a factor equal to the number of pivoted columns.

Question 48Data Preparation

A column headed Amount contains numbers, blank cells and the text n/a. How does Tableau classify the field on connection?

  1. Number (Whole), with n/a converted to zero
  2. Boolean, because the column mixes value types
  3. Number (Decimal), with n/a converted to null
  4. String, because the column contains non-numeric values Correct answer.

Explanation

Tableau infers a single data type from all values in a column, and any non-numeric text forces the field to be a string. Blanks and numbers alone would have produced a numeric type.

Question 49Data Preparation

Where can a custom SQL query be used in the Tableau data model?

  1. In a blend as the secondary source only
  2. Inside a calculated field that returns a table
  3. In the physical layer, as a table within the physical table Correct answer.
  4. In the logical layer, joined to other logical tables by a relationship

Explanation

Custom SQL is a table-level object that resides in the physical layer alongside other physical tables. The logical layer holds logical tables and relationships, where custom SQL is not supported.

Question 50Data Preparation

Rows are deleted from the source table after an extract has been created. An incremental refresh is then run. What is the result?

  1. The deleted rows are removed because incremental refresh reconciles deletions.
  2. The deleted rows are hidden but still stored in the extract.
  3. The deleted rows remain in the extract until a full refresh is run. Correct answer.
  4. The extract fails and must be recreated from scratch.

Explanation

An incremental refresh adds new rows and updates changed rows but does not detect deletions, so removed source rows persist in the extract. A full refresh rebuilds the extract and clears them.