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Tableau TDA-C01, also known as the Tableau Certified Data Analyst Certification Exam, is a comprehensive assessment of a candidate's skills in data analysis using Tableau. Tableau Certified Data Analyst (TDA-C01日本語版) certification exam is designed to evaluate an individual's proficiency in using Tableau to visualize, analyze and interpret data. Tableau Certified Data Analyst (TDA-C01日本語版) certification is considered a mark of distinction for those seeking to stand out in the field of data analysis.

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The TDA-C01 exam consists of 36 multiple-choice questions that must be completed within 120 minutes. TDA-C01-JPN exam covers various topics such as data connection, data preparation, data analysis, and data visualization. Tableau Certified Data Analyst (TDA-C01日本語版) certification exam assesses the candidate's ability to use Tableau Desktop to create and publish interactive visualizations, perform calculations, and solve real-world data problems. The Tableau TDA-C01 certification is a valuable credential for data analysts who want to advance their career by demonstrating their proficiency in Tableau data analysis and visualization.

Tableau TDA-C01 is a certification exam that is designed to test the proficiency of data analysts in using Tableau software. Tableau is a powerful data visualization tool that enables businesses to analyze and interpret large amounts of data. Tableau Certified Data Analyst (TDA-C01日本語版) certification exam is intended to validate the skills and knowledge of data analysts in using Tableau to create visualizations and dashboards, as well as in interpreting and analyzing data.

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Achieving the Tableau TDA-C01 certification demonstrates a candidate's ability to use Tableau software to solve complex data problems and effectively communicate insights from data. Tableau Certified Data Analyst (TDA-C01日本語版) certification is recognized by top companies and organizations worldwide, making it a valuable asset for professionals looking to advance their careers in the field of data analysis. With the increasing demand for skilled data analysts, the Tableau TDA-C01 certification can give candidates a competitive edge in the job market and open up new career opportunities.

Reference: https://www.tableau.com/learn/certification/tableau-certified-data-analyst-exam-guide

Tableau TDA-C01日本語 Exam Syllabus Topics:

SectionWeightObjectives
Create Content26%- Dashboards and Stories
  • 1. Story points creation
    • 2. Dashboard layout and containers
      - Dashboard Interactivity
      • 1. Navigation and parameter actions
        • 2. User guidance and tooltips
          • 3. Filters, actions, and highlights
            - Visualization Creation
            • 1. Bar, line, pie, scatter, histogram, treemap, box plot, etc.
              • 2. Sorting and chart formatting
                - Dashboard Formatting
                • 1. Annotations and padding
                  • 2. Color, fonts, shapes
                    • 3. Responsive layouts
                      Publish and Manage Content9%- Scheduling and Automation
                      • 1. Tableau Prep workflow scheduling
                        • 2. Data extract refresh scheduling
                          - Content Management
                          • 1. Alerts and subscriptions
                            - Publishing
                            • 1. Export and print content
                              • 2. Publish workbooks and data sources
                                Explore and Analyze Data41%- Table Calculations
                                • 1. Percent of total and percent difference
                                  • 2. Ranking and percentile
                                    • 3. Running total and moving average
                                      - Calculated Fields
                                      • 1. Type conversions
                                        • 2. FIXED LOD expressions
                                          • 3. Aggregations
                                            • 4. Date, string, numeric, logical calculations
                                              - Filters and Parameters
                                              • 1. Context filters
                                                • 2. Top N / conditional filters
                                                  • 3. Parameters for interactivity
                                                    • 4. Dimension and measure filters
                                                      - Data Structure and Analytics
                                                      • 1. Sets, groups, hierarchies, bins
                                                        • 2. Geographic mapping (heat, symbol, filled maps)
                                                          • 3. Reference lines, bands, distributions
                                                            • 4. Forecasting and trend analysis
                                                              Connect to and Transform Data24%- Data Connections
                                                              • 1. Connect to relational databases and spreadsheets
                                                                • 2. Live vs extract connections
                                                                  • 3. Custom SQL usage
                                                                    • 4. Connect to data sources
                                                                      - Data Preparation
                                                                      • 1. Pivoting, splitting, Data Interpreter
                                                                        • 2. Joins, unions, relationships, blending
                                                                          • 3. Data cleaning and validation
                                                                            - Field Customization
                                                                            • 1. Discrete vs continuous fields
                                                                              • 2. Data types and field properties
                                                                                • 3. Dimensions vs measures
                                                                                  • 4. Aliases and renaming fields
                                                                                    - Tableau Prep Transformations
                                                                                    • 1. Filtering and restructuring data
                                                                                      • 2. Aggregations and shaping data

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