TABLEAU
1. What are the different data connection options available in Tableau?
Tableau provides various data connection options, including Excel spreadsheets, text files, databases (such as SQL
Server, Oracle, MySQL), and web data connectors.
2. How can you create a calculated field in Tableau?
To create a calculated field in Tableau, you can right-click in the data pane, select "Create Calculated Field," and then
enter the desired formula or expression using Tableau's calculation syntax.
3. What is the difference between a dimension and a measure in Tableau?
In Tableau, a dimension is a categorical or qualitative variable that represents the characteristics or attributes of the
data, while a measure is a quantitative or numerical variable that can be aggregated or summarized.
4. What is the purpose of a parameter in Tableau?
Parameters in Tableau allow users to define dynamic values that can be used to control various aspects of the
visualization, such as filtering data, changing calculations, or modifying colors, like creating a parameter for top 5
companies and bottom 5 companies.
5. How can you perform data aggregation in Tableau?
Tableau provides various aggregation functions, such as SUM, AVG, MAX, MIN, COUNT, etc., which can be applied to
measure fields. To perform aggregation, you can drag a measure field to the visualization and choose the desired
aggregation function., can create a calculated field or table calculation
6.
How Will You Understand Dimensions and Measures?
Dimensions
Measures
1. Dimensions contain qualitative values (such
as names, dates, or geographical data)
2. You can use dimensions to categorize,
segment, and reveal the details in your
data.
3. Example: Category, City, Country, Customer
ID, Customer Name, Order Date, Order ID
1. Measures contain numeric, quantitative
values that you can measure (such as Sales,
Profit)
2. Measures can be aggregated
3. Example: Profit, Quantity, Rank, Sales, Sales
per Customer, Total Orders
In Tableau, a dimension is a categorical or qualitative variable that represents the characteristics or attributes of the
data, while a measure is a quantitative or numerical variable that can be aggregated or summarized.
7. Differentiate discrete and continuous data roles in Tableau
Discrete data roles consist of values that are separate and distinct. Discrete data roles can take individual values
within a range. For Example – cancer patients in the hospital, no. of threads in a sheet, state. Discrete values are
displayed as blue icons in the data window and blue pills on shelves. Discrete fields can be sorted.
Continuous data roles consist of any value within the finite or infinite intervals. For Example – age, unit price, order
quantity. Continuous values displayed as green icons in the data window and green pills on shelves. Continuous fields
cannot be sorted.
Tableau represents data depending on whether the field is discrete (blue) or continuous (green)
8. What is the Difference Between Joining and Blending?
Combining the data from two or more different sources is data blending, such as Oracle, Excel, and SQL Server. In
data blending, each data source contains its own set of dimensions and measures.
Combining the data between two or more tables or sheets within the same data source is data joining. All the
combined tables or sheets contain a common set of dimensions and measures.
9. What is the Difference Between Treemaps and Heat Maps?
Heat Maps
A Heat map is used to compare categories using color and size. In this, we can distinguish two measures. A heat map
is not only defined by color, but you can also use its size.
Tree Maps
A Treemap is used to represent hierarchical data. The space in the view is divided into rectangles that are sized and
ordered by a measure.
10. What Do You Understand the Blended Axis?
Blended Axis is used to blend two measures that share an axis when they have the same scale.
11. What is the Use of Dual-axis?
Dual Axis allows you to compare measures, and this is useful when you want to compare two measures that have
different scales.
12. What is the Level of Detail (LOD) Expression?
A level of detail expression is used to run complex queries involving many dimensions at the data source level instead
of bringing all the data to Tableau interface.
A heatmap is a type of data visualisation that uses different shades of colours to show a data set. The darkest
shade of a particular colour shows an extreme value (high intensity or density). Usually, it is used to compare two
or more measurements.
A quick way to use a heatmap would be to learn about the human body's structure and see how warm it is based
on the temperature of different organs. If the red and yellow colours are used, the red parts will show where the
temperature is the highest.
13. In Tableau, what are aggregation and disaggregation?
Aggregation is the simple idea of taking the average of the values in a given column of a data set. If a report shows
how the price of a product has changed over time, aggregation can help find its average value. Most of the time,
Tableau automatically groups a set of data.
The opposite of averaging is disaggregation, which can be helpful if a user wants to look at each data point
separately. You can also use both grouped and ungrouped data in the same worksheet.
12. Difference between Tableau and Power BI?
Key Difference between Power BI and Tableau
Power BI and Tableau are both powerful business intelligence tools that enable data visualization and analysis. While
they have some similarities, there are key differences between the two:
User Interface: Tableau has a more user-friendly and intuitive interface, with drag-and-drop functionality and easierto-use visuals. Power BI can take a bit more time to learn but provides more robust functionality for advanced users.
Data Integration: Power BI is more tightly integrated with Microsoft products, such as Excel and SQL Server, whereas
Tableau can connect to a wider range of data sources, including cloud-based databases and web services.
Pricing: Power BI offers a more affordable pricing structure, with a free version and lower-cost paid options. Tableau,
on the other hand, can be more expensive, especially for enterprise-level solutions.
Customization: Tableau provides more advanced customization options for dashboards and visualizations, whereas
Power BI is more limited in this regard.
Collaboration: Power BI has more collaboration features built-in, such as co-authoring and commenting, whereas
Tableau requires third-party tools to achieve similar functionality.
Ownership and Pricing: Power BI is a Microsoft product licensed on a per-user basis, while Tableau is owned by
Salesforce and licensed on a per-user or per-server basis.
Data Integration: Power BI is tightly integrated with other Microsoft products like Excel, Azure, and Dynamics 365,
while Tableau has more options for integrating with third-party applications and data sources.
Visualization Capabilities: Tableau is known for its exceptional visualization capabilities and has more advanced
charting options. In contrast, Power BI has a more user-friendly interface for creating basic charts and visualizations.
Data Modeling: Power BI has more robust data modeling and ETL (Extract, Transform, Load) capabilities than
Tableau, making it a better choice for data manipulation and analysis.
Collaboration: Tableau has more robust collaboration features, including creating and sharing interactive dashboards
with other users, while Power BI is more focused on individual user analysis.
Mobile App: Power BI has a more robust mobile app for iOS and Android devices, while Tableau's mobile app is more
limited in functionality.
READ ABOUT JOINS
Grouping is used to group the dimensions together