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Tableau TDS-C01 Exam Questions
- Topic 1: Connecting to and Preparing Data: This section of the exam measures the skills of Tableau Developers and covers the fundamentals of data connection and preparation in Tableau. It includes creating live connections and extracts, understanding their differences, and saving metadata properties. Candidates should be able to create data sources with multiple connections and manage the data model by adding relationships, joins, and unions. The exam also tests knowledge of data property management, including renaming fields, assigning aliases and geographic roles, changing data types, and modifying default properties. A key skill measured is the ability to create an extract from a data source, which optimizes performance for large datasets.
- Topic 2: Exploring and Analyzing Data: Data Analysts are evaluated on their ability to create and manipulate various chart types in Tableau. This domain covers the creation of basic charts such as bar charts, line charts, scatterplots, and maps. It also includes more advanced visualizations like combined axis charts, dual axis charts, and density maps.
- Topic 3: Sharing Insights: This section measures the skills of Tableau Developers in presenting and sharing data insights effectively. It covers formatting views for presentation, including the use of colors, fonts, shapes, and animations. Candidates should be able to create and modify dashboards by adding worksheets, interactive elements, and dashboard actions. The exam also tests knowledge of creating device-specific dashboards and stories.
- Topic 4: Understanding Tableau Concepts: Data Analysts are evaluated on their understanding of fundamental Tableau concepts in this domain. It covers the distinctions between dimensions and measures, discrete and continuous fields, and their implications in visualizations. Candidates should comprehend how discrete and continuous fields are displayed differently and the impact of using discrete date parts versus continuous date values. The exam also tests knowledge of aggregations, including the default aggregation for measures and how aggregated measures change when dimensions are added to a view.
Free Tableau TDS-C01 Exam Actual Questions
Note: Premium Questions for TDS-C01 were last updated On 31-07-2025 (see below)
______________ refers to the level of detail for a piece of data, wherever you are looking.
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.
Which one of the following is a dimension?
Measure Names is a dimension. Latitude, Longitude, and Number of records are all measures.
__________ is a technique in Tableau which will identify marks with similar characteristics
Cluster analysis partitions marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters.
Broadly speaking, after an importing a dataset in Tableau Desktop, all fields in it are broken down into _______________________
When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.
Further,
What is created by a calculated field that has a formula of SUM(Sales)/SUM(Profit)?
a calculated field that has a formula of SUM(Sales)/SUM(Profit) is a measure, because it returns a numeric value that can be aggregated and used for analysis. A parameter is a user-defined variable that can be used in calculations or filters. A dimension is a categorical field that can be used to group or slice data. A set is a subset of data based on some condition.
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