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Free TDS-C01 Exam Braindumps (page: 4)

Page 3 of 56
PDF with 317 Questions

True or False: All rows from both tables are returned in an INNER JOIN

  1. True
  2. False

Answer(s): B

Explanation:

The INNER JOIN keyword selects all rows from both tables as long as there is a match between the columns. Consider 2 tables "Orders" and "Customers".
If there are records in the "Orders" table that do not have matches in "Customers", these orders will not be shown!


Reference:

https://www.w3schools.com/sql/sql_join_inner.asp



Is SUM a table calculation?

  1. Yes
  2. No

Answer(s): B

Explanation:

SUM is an aggregate function, not a table calculation!
A table calculation is a transformation you apply to the values in a visualization. Table calculations are a special type of calculated field that computes on the local data in Tableau. They are calculated based on what is currently in the visualization and do not consider any measures or dimensions that are filtered out of the visualization.

The most common Table calculations are:
Running Total
Percent Difference
Difference
Percent of Total
Rank
Percentile


These can be calculated using: Table(across), Cell, or Specific dimensions!


Reference:

https://help.tableau.com/current/pro/desktop/en-us/calculations_tablecalculations_definebasic_runningtotal.htm



By default, measures placed in a view are aggregated by ____________.

  1. COUNT
  2. AVERAGE
  3. MEDIAN
  4. SUM

Answer(s): D

Explanation:

By default, measures placed in a view are aggregated by SUM, which means that the data for that field in all of the rows is combined. Measures can also be aggregated as average, median, count, or count distinct.


Reference:

https://help.tableau.com/current/pro/desktop/en-us/calculations_aggregation.htm



_____________ refers to the level of detail for a piece of data, wherever you are looking.

  1. Data Cleanliness
  2. Data granularity
  3. Data connectivity
  4. Data LOD

Answer(s): B

Explanation:

Data is generated and analyzed at many different levels of granularity. Granularity is the level of detail of the data. For example, when looking at graduation data, granularity would describe whether a row in the data set represents a single person or the graduating class of a university.


Reference:

https://www.tableau.com/about/blog/2018/6/data-prep-101-what-aggregate-function-and-how-do-you-combine-aggregated-data-89244






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