Tableau TDS-C01 Practice Test - Questions Answers, Page 3

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.

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.

A bullet graph is a variation of a bar graph developed to replace dashboard gauges and meters. A bullet graph is useful for comparing the performance of a primary measure to one or more other measures.

Therefore, we need at least 2 measures for creating bullet graphs.

By default, all of the above mentioned are stored in Documents -> My Tableau Repository

Tableau auto-generates :

1 Dimension - Measure Names

4 Measures - Latitude, Longitude, Number of records, Measure Values

Starting with Tableau 2020.2, every table in a data source has a Count field, in the form of NameofTable(Count). The table count field is an automatically generated, calculated field. (THIS IS NOT PRESENT IN VERSION 2020.1 ON WHICH THE EXAM IS CURRENTLY BASED)

It is possible to join a maximum of 32 tables in Tableau!

Extracts are advantageous for several reasons:

1) Supports large data sets: You can create extracts that contain billions of rows of data.

2) Fast to create: If you're working with large data sets, creating and working with extracts can be faster than working with the original data.

3) Help improve performance: When you interact with views that use extract data sources, you generally experience better performance than when interacting with views based on connections to the original data.

4) Support additional functionality: Extracts allow you to take advantage of Tableau functionality that's not available or supported by the original data, such as the ability to compute Count Distinct.

5) Provide offline access to your data: Extracts allow you to save and work with the data locally when the original data is not available. For example, when you are traveling.

To work with the MOST up-do-date data, use a live connection instead!

IMPORTANT QUESTION, PAY ATTENTION

By default, all filters that you set in Tableau are computed independently. That is, each filter accesses all rows in your data source without regard to other filters. However, you can set one or more categorical filters as context filters for the view. You can think of a context filter as being an independent filter. Any other filters that you set are defined as dependent filters because they process only the data that passes through the context filter.

You may create a context filter to:

1) Improve performance -- If you set a lot of filters or have a large data source, the queries can be slow. You can set one or more context filters to improve performance.

2) Create a dependent numerical or top N filter -- You can set a context filter to include only the data of interest, and then set a numerical or a top N filter.

After making changes to Data, we can save that new data source as a .tds file. To do so, go to data menu on top and then choose your current connected data source. Then next click on Add to Saved Data sources. This will save all calculated fields, changes to fields etc. It will be saved in My Tableau Repository -> Mydatasources. This will then also appear on Tableau Home Page under saved data sources like SampleSuperStore.

Note: Data source files do not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you've made on top of the actual data such as changing default properties, creating calculated fields, adding groups, and so on.

.twb and .twbx are not the BEST solutions since the questions nowhere mentions that we need to store our workbooks as well.

.twm is a bookmark which contains a single worksheet and are an easy way to quickly share your work.