Tableau Certified Consultant TCC-C01 Dumps

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Are you wondering how to best prepare for your TCC-C01 Tableau Certified Consultant exam? Passcert designed high-quality Tableau Certified Consultant TCC-C01 Dumps that are specifically tailored according to the topics that are of utmost importance for passing the Tableau TCC-C01 exam. After studying the Tableau Certified Consultant TCC-C01 Dumps, you will experience a marked improvement in your understanding of the exam concepts. They are particularly beneficial for reinforcing weak concepts, thereby ensuring you are thoroughly prepared before you make the final attempt at the exam. This will not only boost your confidence but also significantly increase your chances of passing the Tableau Certified Consultant exam.

Tableau Certified Consultant TCC-C01 Dumps

About the Tableau Certified Consultant Exam

The Tableau Certified Consultant certification is intended for individuals who engage with customers to lead the design of an analytics solution within the Tableau platform. Projects may be scoped to the executive level rather than just the business unit level. They provide longer term, strategic recommendations for analytics and handle complex performance issues independently. They solve very complex data issues.

This credential validates both core Tableau knowledge and hands-on development skills of employees, partners, customers, and freelancers, who need to work with various Tableau products including Tableau Prep, Desktop, Cloud, Server, and Bridge. There are no prerequisites for the exam. Upon successful completion of this exam, candidates are awarded the title of Tableau Certified Consultant. This title is valid for two years.

Audience Description: Tableau Certified Consultant

Candidates for this exam engage with customers to lead the design of an analytics solution within the Tableau platform. They can work through very complex data issues. Projects may be scoped to the executive level rather than just the business unit level. They provide longer term, strategic recommendations for analytics and handle complex performance issues independently.

The Consultant typically has a minimum 1 year of experience with Tableau and Tableau products including Tableau Prep, Desktop, Cloud, Server, and Bridge, and has been involved in at least two implementations. The Consultant has the skills to pass Tableau Desktop Specialist (TDS) and Tableau Certified Data Analyst (TCDA) certification exams. This exam is the advancement of that skillset. Candidates will not be tested on the level of the TDS and TCDA exams because they are assumed to possess the competencies covered in those exams.

Exam Overview

Knowledge-based: 40-45 multiple-choice and multiple-select items

Performance-based: 6-8 hands-on lab tasks

Time Limit: 120 minutes (includes 3 minutes for reviewing the NDA and 5 minutes for tutorial).

Language(s) Offered: English

Passing Score: 750

Prerequisite: None required

Registration fee: USD $250 plus applicable taxes as required by local law

Exam Outline

Domain 1: Evaluate Current State       28%

1.1 Map current state of analytics to future state

1.1.1 Evaluate existing reports, including volume, gap analysis, performance, and data accuracy

1.1.2 Map existing reports, data products, and business needs to Tableau capabilities

1.1.3 Translate analytical requirements into Tableau context by using best practices

1.1.4 Recommend whether to use Tableau Server or Tableau Cloud, including migration

1.2 Evaluate current data structures

1.2.1 Evaluate whether existing data supports business needs

1.2.2 Evaluate lineage of existing data structures

1.2.3 Evaluate existing data structures for performance risks

1.2.4 Evaluate existing data structures for performance enhancement opportunities

Domain 2: Plan and Prepare Data Connections      19%

2.1 Plan for data transformation

2.1.1 Recommend an appropriate data storage method, data structure, and strategy

2.1.2 Recommend an appropriate tool to transform data, including Tableau Desktop, Tableau Prep, or an ETL product

2.1.3 Identify impact of static and responsive calculations in Tableau Prep and Tableau workbooks

2.1.4 Specify the requirements for minimum level of granularity

2.2 Design a row-level security (RLS) data structure

2.2.1 Implement RLS and an entitlement table

2.2.2 Identify group functions versus user functions

2.2.3 Implement hierarchies to support RLS

2.2.4 Compare RLS approaches

2.3 Plan and implement advanced connections to data

2.3.1 Recommend an appropriate method to connect to data, such as Web Data Connectors, web extract APIs, custom SQL, or ODBC

2.3.2 Create connections by using Tableau Bridge

2.3.3 Recommend how to prepare data to meet specific requirements, including shaping and combining

2.3.4 Specify aggregation level and strategy for data sources in Tableau products (Tableau Desktop, Tableau Prep, Tableau Cloud, Tableau Server)

2.3.5 Identify the minimum fields required for analysis

2.3.6 Troubleshoot complex data issues and connections

Domain 3: Design and Troubleshoot Calculations and Workbooks     39%

3.1 Design analytics for advanced use cases

3.1.1 Recommend when to use an advanced chart type, such as Sankey, chord, radar, tile map, small multiples, and data densification

3.1.2 Plan and implement the necessary calculations for customized charts

3.1.3 Identify the effect of the Tableau order of operations on calculations

3.1.4 Troubleshoot issues caused by the Tableau order of operations

3.1.5 Plan and implement advanced techniques to build interactivity into dashboards, such as dynamic URL actions, parameter actions, filter actions, and sheet swapping

3.1.6 Identify use cases for augmented analytics, such as Ask Data, Explain Data, and Data Stories

3.2 Design workbooks to optimize performance

3.2.1 Identify and resolve resource-intensive queries

3.2.2 Maximize caching for Tableau Server

3.2.3 Identify and resolve performance issues caused by calculations such as string comparisons, IF THEN statements, and Level of Detail (LOD) expressions

3.2.4 Recommend calculations that should be moved upstream of Tableau

3.2.5 Interpret and resolve issues by using performance recordings

3.2.6 Identify and resolve performance issues caused by design elements such as number of sheets, number of filters, and image size

3.3 Implement advanced calculations that include multiple steps

3.3.1 Implement aggregations that include dimensions

3.3.2 Implement advanced table calculations, such as window, nested table, or multi-directional

3.3.3 Implement advanced date functions, such as fiscal calendars

3.3.4 Implement advanced LODs, such as nested LODs

3.3.5 Implement combinations of advanced calculations

3.3.6 Troubleshoot advanced calculations

Domain 4: Establish Governance and Support Published Content      14%

4.1 Recommend and apply a Tableau governance strategy

4.1.1 Map an organization’s governance requirements to Tableau features and capabilities

4.1.2 Recommend a strategy for securing access to content

4.1.3 Recommend a strategy for organizing content, such as by function, by organization, and by role

4.1.4 Recommend a strategy for ensuring data quality, including certifying data sources, minimizing data proliferation, and configuring data quality warnings

4.1.5 Evaluate compliance with a governance strategy by using Data Catalog, including Data Lineage

4.2 Design custom administrative views

4.2.1 Interpret the repository schema and event types

4.2.2 Specify insights that require a custom administrative view

4.2.3 Specify appropriate permissions to create administrative views

4.3 Recommend a content distribution strategy

4.3.1 Map publishing requirements to features and capabilities of Tableau

4.3.2 Recommend an approach for the workbook lifecycle, including building, testing, deployment, distribution, and maintenance

4.3.3 Recommend a version control strategy within Tableau

4.4 Identify and resolve errors external to Tableau

4.4.1 Identify and resolve connection authentication and network access

4.4.2 Identify and resolve update failures that originate from the source system

4.4.3 Identify other issues that originate from outside Tableau, such as platform or network outage

Share Tableau Certified Consultant TCC-C01 Free Dumps

1. A client has many published data sources in Tableau Server. The data sources use the same databases and tables. The client notices different departments give different answers to the same business questions, and the departments cannot trust the data. The client wants to know what causes data sources to return different data.

Which tool should the client use to identify this issue?

A. Tableau Prep Conductor

B. Ask Data

C. Tableau Catalog

D. Tableau Resource Monitoring Tool

Answer: C

2. A client has a published data source in Tableau Server and they want to revert to the previous version of the data source. The solution must minimize the impact on users.

What should the consultant do to accomplish this task?

A. Request that a server administrator restore a Tableau Server backup.

B. Delete and recreate the data source manually.

C. Select a previous version from Tableau Server, download it, and republish that data source.

D. Select a previous version from Tableau Server, and then click Restore.

Answer: D

3. A Tableau Cloud client has requested a custom dashboard to help track which data sources are used most frequently in dashboards across their site.

Which two actions should the client use to access the necessary metadata? (Choose two)

A. Connect directly to the Site Content data source within the Admin Insights project.

B. Query metadata through the GraphiQL engine.

C. Access metadata through the Metadata API.

D. Download metadata through Tableau Catalog.

Answer: B, C

4. A client notices that while creating calculated fields, occasionally the new fields are created as strings, integers, or Booleans. The client asks a consultant if there is a performance difference among these three data types.

What should the consultant tell the customer?

A. Strings are fastest, followed by integers, and then Booleans.

B. Integers are fastest, followed by Booleans, and then strings.

C. Strings, integers, and Booleans all perform the same.

D. Booleans are fastest, followed by integers, and then strings.

Answer: B

5. A new Tableau user created a simple dashboard on Tableau Server using supply chain data. Now, the user wants to know if they created the dashboard in accordance with specific performance best practices.

Which approach should the consultant recommend for the client to make this determination?

A.Use inbuilt dashboards in Tableau Server to troubleshoot the performance.

B.Use Performance Recording on Tableau Server.

C.Use Performance Recording in Tableau Desktop.

D.Run Workbook Optimizer.

Answer: D

6. A client requests a published Tableau data source that is connected to SQL Server. The client needs to leverage the multiple tables option to create an

extract. The extract will include partial data from the SQL Server data source.

Which action will reduce the amount of data in the extract?

A.Use an extract filter.

B.Aggregate the extract to the visible dimensions.

C.Define the filters by using custom SQL.

D.Set up the extract as an incremental refresh.

Answer: A

7. A consultant is designing a dashboard that will be consumed on desktops, tablets, and phones. The consultant needs to implement a dashboard design that provides the best user experience across all the platforms.

Which approach should the consultant take to achieve these results?

A.Build one dashboard that has desktop, tablet, and phone layouts, and fix the size of the layouts.

B.Build one dashboard and fix the size of the dashboard.

C.Build one dashboard and set the size to Automatic.

D.Build one dashboard for each type of device and fix the size of the layouts.

Answer: A

8. A client has a published dashboard. They change the dashboard and then republish it. Now, usersreport that their web browser bookmarks to the dashboard are broken.

What are two possible causes for this issue? (Choose two)

A.New credentials were embedded into the data source.

B.The dashboard was published to a different project.

C.Tableau Server was upgraded.

D.The dashboard was published with a new name.

Answer: B, D

9. A client builds a dashboard that presents current and long-term stock measures. Currently, the data is at a daily level. The data presents as a bar chart that presents monthly results over current and previous years. Some measures must present as monthly averages.

What should the consultant recommend to limit the data source for optimal performance?

A. Move calculating averages to data layer and aggregate dates to monthly level.

B. Limit data to current and previous years and leave data at daily level to calculate the averages in the report.

C. Limit data to current and previous years, move calculating averages to data layer, and aggregate dates to monthly level.

D. Limit data to current and previous years as well as to the last day of each month to eliminate the need to use the averages.

Answer: C

10. A consultant creates a histogram that presents the distribution of profits across a client’s customers. The labels on the bars show percent shares. The consultant used a quick table calculation to create the labels.

Now, the client wants to limit the view to the bins that have at least a 15% share. The consultant creates a profit filter but it changes the percent labels.

Which approach should the consultant use to produce the desired result?

A.Use a calculation with TOTAL() function instead of a quick table calculation.

B.Add the [Profit] filter to the context.

C.Filter with a table calculation WINDOW_AVG(MIN([Profit]), first(), last())

D.Filter with the table calculation used to create labels.

Answer: B