TDS-C01ウェブトレーニング - Tableau Desktop Specialistに合格するための最も鋭い刀

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Tableau TDS-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Exploring & Analyzing Data35%- Use filters, sets, groups
  • 1. Filter by dimension, measure, date, context
    • 2. Create and use sets and groups
      - Create basic visualizations
      • 1. Tables: crosstab, highlight table
        • 2. Charts: bar, line, scatter, map, dual-axis
          - Create calculations
          • 1. Level of Detail (LOD) expressions
            • 2. Basic calculations: string, date, math, logic
              Topic 2: Understanding Tableau Concepts15%- Data types and roles
              - Tableau file types and structure
              - Dimensions vs Measures, Discrete vs Continuous
              Topic 3: Sharing Insights & Building Dashboards25%- Build interactive dashboards
              • 1. Add sheets, filters, actions, parameters
                • 2. Design for different devices
                  - Create stories
                  • 1. Combine visualizations into stories
                    - Publish and share content
                    • 1. Publish to Tableau Server / Online / Public
                      • 2. Export: image, PDF, PowerPoint
                        Topic 4: Connecting to & Preparing Data25%- Prepare and transform data
                        • 1. Customize fields: type, alias, discrete/continuous
                          • 2. Shape data: filter, group, aggregate
                            • 3. Combine data with joins, unions, blends
                              - Connect to data sources
                              • 1. Use Data Interpreter, pivot, split
                                • 2. Live connections and extracts
                                  • 3. Save and use .TDS files

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                                    Tableau Desktop Specialist 認定 TDS-C01 試験問題 (Q112-Q117):

                                    質問 # 112
                                    We can use ______________ as a static tool to open and interact with packaged workbooks with extracted data sources that have been created in Tableau Desktop.

                                    正解：C

                                    解説：
                                    The word 'static tool' gives it away.
                                    According to the official website :


                                    質問 # 113
                                    What are three benefits of using an extract as compared to a live connection to a data source? Choose three.

                                    正解：A、C、D

                                    解説：
                                    There are three benefits of using an extract as compared to a live connection to a data source:
                                    A live connection to a data source can be slow due to network and user traffic, whereas a connection to an extract improves performance. An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can reduce the load on the data source and speed up queries.
                                    Extracts are stored in memory (RAM), resulting in faster query performance as compared with live data connections. When you use an extract, Tableau loads the data into memory and optimizes it for analysis. This allows Tableau to perform calculations and aggregations faster than with live connections.
                                    Calculated fields perform better in workbooks connected to extracts than in workbooks with live connections to a data source. Calculated fields are custom fields that you create using formulas or expressions. When you use an extract, Tableau can process calculated fields more efficiently than with live connections.


                                    質問 # 114
                                    Which type of filter affects a fixed Level of Detail (LOD) expression?

                                    正解：B

                                    解説：
                                    In Tableau, a Fixed Level of Detail (LOD) expression calculates values at a specific level of granularity, regardless of the dimensions in the view. The computation of a fixed LOD expression can be influenced by a context filter. A context filter serves as a primary filter, setting the context for the rest of the filters in the view.
                                    When a context filter is applied, it effectively changes the level at which the fixed LOD expression is computed, thereby affecting its outcome. Other types of filters, such as table calculation, measure, and dimension filters, do not have this influence on fixed LOD expressions.


                                    質問 # 115
                                    If you decide you want to see all of the marks in the view at the most detailed level of granularity, you can
                                    __________________ the view.

                                    正解：E

                                    解説：

                                    The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.
                                    For a complete list of the available aggregations, check out - List of Predefined Aggregations in Tableau.
                                    The level of detail is determined by the dimensions in your view-for information about the concept of level of detail, see How dimensions affect the level of detail in the view.
                                    Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.
                                    Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.


                                    質問 # 116
                                    Which of the following lets you group related dashboard items together so you can quickly position them?

                                    正解：D

                                    解説：
                                    Layout containers let you group related dashboard items together so you can quickly position them. As you change the size and placement of items inside a container, other container items automatically adjust


                                    質問 # 117
                                    ......

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