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The TDS-C01 exam is a multiple-choice exam that tests the candidate's knowledge and understanding of Tableau Desktop. TDS-C01 Exam consists of 36 questions and has a time limit of 120 minutes. TDS-C01 exam covers various topics related to Tableau Desktop, including data connection, data preparation, visualization, analysis, and dashboard creation. TDS-C01 exam is conducted online and can be taken in English, Japanese, or Simplified Chinese.
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As the tech industry continues to evolve and adapt to new technologies, professionals who hold the Tableau Desktop Specialist (TDS-C01) certification are better equipped to navigate these changes and stay ahead of the curve, increasing their value to employers and clients. In today's fast-paced and ever-changing Tableau sector, having the Tableau Desktop Specialist (TDS-C01) certification has become a necessary requirement for individuals looking to advance their careers and stay competitive in the job market.
The TDS-C01 exam consists of 36 multiple-choice questions and has a time limit of 120 minutes. TDS-C01 exam covers a wide range of skills, including connecting to and preparing data, creating and editing visualizations, using calculations, and publishing and sharing content. TDS-C01 exam is designed to assess an individual's ability to use Tableau Desktop to solve real-world data problems. Upon passing the exam, individuals will receive a digital badge that can be displayed on their LinkedIn profile or resume, indicating their proficiency in Tableau Desktop. The TDS-C01 Certification is a recognized credential in the data visualization industry and can help individuals stand out in a competitive job market.
NEW QUESTION # 27
You have the following data.
You want to sort each category's sub-category by ascending sales.
Which sort option should you use?
Answer: C
Explanation:
A nested sort allows you to sort data within each category by a secondary field, such as sub- category sales in this case. By using a nested sort in Tableau, each sub-category within a category will be sorted by Sales in ascending order, providing the desired hierarchy within each main category. Other options, like manual sort and data source order, would not automatically achieve this within-category sorting by sales, and field sort does not offer nested functionality by default.
NEW QUESTION # 28
Which three statements accurately describes the capabilities of dashboard actions? (Choose three.)
Answer: B,C,D
Explanation:
Dashboard actions in Tableau have several capabilities:
- They can involve multiple source and target sheets, allowing actions to span across various views within a dashboard.
- Actions can be set to run on Hover, Select, or Menu, providing different interaction methods for triggering the action.
- Actions can perform operations like Filter, Highlight, or Go to URL, enhancing interactivity by allowing users to drill down or navigate to external content.
NEW QUESTION # 29
What does the following marker/icon do in Tableau?
Answer: C
Explanation:
The correct answer is Toggle the highlighting ON/OFF. If selected, whichever value you choose from this legend will be highlighted in the view. However, if it is deselected, then even if you choose a value in the Legend, it will NOT be highlighted.
See below:
NEW QUESTION # 30
True or False: We can disaggregate the data, to see all of the marks in the view at the most detailed level of granularity
Answer: B
Explanation:
Whenever you add a measure to your view, an aggregation is applied to that measure by default. This default is controlled by the Aggregate Measures setting in the Analysis menu.
If you decide you want to see all of the marks in the view at the most detailed level of granularity, you can disaggregate the view. Disaggregating your data means that Tableau will display a separate mark for every data value in every row of your data source.
To disaggregate all measures in the view:
Clear the Analysis >Aggregate Measures option. If it is already selected, click Aggregate Measures once to deselect it.
NEW QUESTION # 31
______________ refers to the level of detail for a piece of data, wherever you are looking.
Answer: 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.
NEW QUESTION # 32
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