TABLEAU SERVER UPDATED EXAM
SCRIPT 2026 TEST PAPER
QUESTIONS AND SOLUTIONS
GRADED A+
◉ Extracts.
Answer: are saved subsets of data that improve performance and take
advantage of Tableau functionality, allowing you to refresh the data on a
regular basis.
◉ Published Data Source.
Answer: the data source can be either a live connection or an extract
◉ Flat files.
Answer: xlsx, csv, pdf, tdsx --.TIFF files are not accessible via tableau
desktop data collection window
◉ Tableau Server.
Answer: customer-managed sharing platform where creators, explorers
and viewers can create, interact, and share content
SQL, Oracle, etc
◉ Tableau Online.
Answer: fully hosted (by tableau) sharing platform where creators,
explorers and viewers can create, interact, and share content
,◉ Tableau Prep.
Answer: desktop based visual ETL program. It enables developers to
connect to data, create workflows, automate jobs and share flows with
others.
◉ Tableau Prep - Connections Pane.
Answer: is on the left side and it's the space where you connect to your
data sources
◉ Tableau Prep - Flow pane.
Answer: at the top and shows a visual representation of each step in the
data prep process
◉ Tableau Prep - Profile pane.
Answer: displays a summary of each field in the data sample
◉ Tableau Prep - Data grid.
Answer: displays a preview of the rows and columns of the data source
Any changes that are made in to profile pane will automatically show in
the data grid
◉ Field type.
Answer: number, date, sting, Boolean or geographic role
, ◉ Alias.
Answer: can only be created for a dimension
◉ full vs. incremental refresh.
Answer: full refresh replaces all of the contents in the extract
An incremental refresh only adds rows that are new since the previous
refresh.
◉ logical layer.
Answer: the canvas for creating relationships between tables
◉ physical layer.
Answer: for creating unions and joins between tables (joins tables
together)
◉ Aggregate.
Answer: rolls up the level of granularity on visible dimensions (used to
reduce data size) **impacts the way your calculations function
◉ relationships.
Answer: create contextually appropriate joins (displayed as flexible
noodles between logical tables)
SCRIPT 2026 TEST PAPER
QUESTIONS AND SOLUTIONS
GRADED A+
◉ Extracts.
Answer: are saved subsets of data that improve performance and take
advantage of Tableau functionality, allowing you to refresh the data on a
regular basis.
◉ Published Data Source.
Answer: the data source can be either a live connection or an extract
◉ Flat files.
Answer: xlsx, csv, pdf, tdsx --.TIFF files are not accessible via tableau
desktop data collection window
◉ Tableau Server.
Answer: customer-managed sharing platform where creators, explorers
and viewers can create, interact, and share content
SQL, Oracle, etc
◉ Tableau Online.
Answer: fully hosted (by tableau) sharing platform where creators,
explorers and viewers can create, interact, and share content
,◉ Tableau Prep.
Answer: desktop based visual ETL program. It enables developers to
connect to data, create workflows, automate jobs and share flows with
others.
◉ Tableau Prep - Connections Pane.
Answer: is on the left side and it's the space where you connect to your
data sources
◉ Tableau Prep - Flow pane.
Answer: at the top and shows a visual representation of each step in the
data prep process
◉ Tableau Prep - Profile pane.
Answer: displays a summary of each field in the data sample
◉ Tableau Prep - Data grid.
Answer: displays a preview of the rows and columns of the data source
Any changes that are made in to profile pane will automatically show in
the data grid
◉ Field type.
Answer: number, date, sting, Boolean or geographic role
, ◉ Alias.
Answer: can only be created for a dimension
◉ full vs. incremental refresh.
Answer: full refresh replaces all of the contents in the extract
An incremental refresh only adds rows that are new since the previous
refresh.
◉ logical layer.
Answer: the canvas for creating relationships between tables
◉ physical layer.
Answer: for creating unions and joins between tables (joins tables
together)
◉ Aggregate.
Answer: rolls up the level of granularity on visible dimensions (used to
reduce data size) **impacts the way your calculations function
◉ relationships.
Answer: create contextually appropriate joins (displayed as flexible
noodles between logical tables)
