Top 15 Frequently Asked Tableau Interview Questions:-

In order to effectively relay analytical knowledge between humans and machines, the art of data visualisation is becoming increasingly important.

Nearly half of the Fortune 500 businesses now use Tableau. Consequently, there has been a growing need for knowledgeable tableau professionals throughout time. Therefore, if you want to begin a profession in data visualisation, enrol in MindMajix Tableau Training.

Here is what we’ve gathered. Tableau interview questions and answers that are frequently asked. This blog’s questions were compiled with the help of tableau subject-matter experts.

Basic Tableau Interview Questions

1. Why is Tableau better than other BI tools? Give reasons.

Tableau is better than other BI tools because-

• It is easy to use.
• It integrates with Python, R and other scripting languages.
• It also provides high reliability and performance and can handle millions of data records.
• It can ingest data from any source and create beautiful dashboards.

2. What is a Parameter in Tableau?

A parameter is a workbook variable in Tableau such as number, date, or string that can replace a constant value in a calculation, filter, or reference line. A parameter allows the end user to change the content that appears in worksheets and dashboards. It can help narrow down the focus of analysis while entering conditions into parameters.

3. Explain the different types of JOINS in Tableau.

There are four types of JOINS in Tableau:

1. INNER JOIN- It is used to join two tables based on the matched common values.
2. LEFT JOIN– It is used to join two tables based on the matched common values and all values in the left table.
3. RIGHT JOIN– It is used to join two tables based on the matched common values and all values in the right table.
4. FULL OUTER JOIN– It is used to join two tables that contain all values from both tables irrespective of the matched common values.

4. What are the advantages and disadvantages of Tableau?

Advantages of Tableau are:

• It has multiple data source connections.
• It is easy to use.
• It has high visualisation capabilities.
• It has high performance i.e. it can operate on a large amount of data.
• It is mobile friendly.

Disadvantages of Tableau are:

• It has a high cost.
• It needs manual effort.
• There is no automatic refreshing of reports.
• It requires knowledge of SQL.
• There is no version control.

5. What is a Filter? Explain different types of filters in Tableau.

Filter is used to segregate the data based on dimensions and reduce the number of records present in a dataset for faster processing.

There are six types of filters in Tableau:

1. Extract Filters- They are used to filter the extracted data from the data sources. These filters are used only if the user extracts the data from the data source. It also helps to lower the queries to the data source.
2. Context Filter- It creates datasets based on the original data sheet and the presets chosen for compiling the data. It helps in applying a relevant, actionable context to the entire data analysis in Tableau.
3. Data Source Filter- It is used to show only essential data sources by restricting the sensitive data. It helps in minimising data feeds for faster processing.
4. Dimension Filter- Filters that are applied on dimensions are called dimension filters. With the help of these filters we can select or deselect the values, or we can perform wildcard selection or condition based selection where we can use complex formulas or simple conditions to filter out data.
5. Measure Filter- Filters that are applied on measurable or quantitative data are called measure filters. The Measure filter has a range of values- At Least, At Most and Special sub filters.
6. Table Filter- This filter can look through data quickly without adding any additional filter to the hidden data.

6. What is the difference between a Tree Map and a Heat Map?

Tree Map

• It is used to show a huge amount of hierarchical structured data.
• The levels in the hierarchy of the tree map are visualised as rectangles containing other rectangles which represent a category in a column.
• A bigger rectangle represents a high frequency category in a column, while a smaller rectangle represents a low frequency category.

Heat Map

• It is a graphical representation of data where values are depicted by colour.
• Heat maps make it easy to visualise complex data and understand it at a glance.
• It uses colour to communicate relationships between data values, which is much harder to understand if presented numerically in a spreadsheet.

7. Differentiate between Joining and Blending.

8. Explain Rank function and Dense_rank function in Tableau.

The Rank Function in Tableau accepts two arguments- aggregated measure and ranking order. The ranking order can be ascending or descending. The ranking order is optional and by default assigned as descending. For example- If the values are 3,5,6,7,7,9 then their corresponding ranks would be 1,2,3,4,4,6 in ascending order.

The Dense_rank function works in a similar manner as the Rank function except it won’t skip the next rank when assigning the same rank to identical values. For example- If the values are 3,5,6,7,7,9 then their corresponding dense ranks would be 1,2,3,4,4,5 in ascending order.

9. What is Rank_modified and Rank_unique function in Tableau?

The Tableau Rank_Modified function will assign the same rank to an identical value. When we have a repeating number, we skip a number and assign the same rank to repeating values. The Highest value will rank as 1, and the following two equal amounts will rank as 3. For example, if we have 6,9,9,14 then the function will return the ranks as 4, 3, 3, 1. The Tableau Rank_UNIQUE function will assign unique ranks to identical values. For example, if we have 3,5,6,7,7,9 then the function will return the ranks as 1,2,3,4,5,6,7 in ascending order.

10. Explain the Level of Detail (LOD) function.

Level of Detail (LOD) functions are used to run queries which are complex, and involve many dimensions at the data source level. The different types of LOD functions are:

1. Fixed LOD- It does not require reference to any other dimensions for computing values using the specified dimensions.
2. Include LOD- It computes values using the specified dimensions in addition to whatever dimensions are in the view.
3. Exclude LOD- It subtracts dimensions from the view level of detail.

11. What is Measure and Dimension in Tableau?

In Tableau, Measures represent quantitative data such as integer, string etc. and are used and analysed by dimensions. While dimensions represent qualitative values to define a particular category. Examples of dimensions are geographical data, product details, countries, etc.

12. How can we handle NULL values in Tableau?

We can handle the NULL values in Tableau in the following ways:

• Using ZN() function- It assigns 0 to NULL values.
• Using IFNULL() function- We can use if conditions to fill NULL values.
• Using ISNULL() function- It tests a numerical column and returns ‘TRUE’ if the expression doesn’t contain valid data (NULL).
• Using filter option- It excludes the NULL values from the view using a filter.
• Using hide NULL indicator- We can use hide NULL indicator by clicking on the bar chart to hide NULL values from the figure.

13. What is Blended Axis and Dual Axis in Tableau?

Blended Axis is used when more than two measures are used in multi-line graphs or charts. For example- Sales, Profit and Discount per Quarter. Dual axis is used when two measures are used in dual lines of graphs or charts. Both axes will be parallel to each other with a different range of values from the source data. For example- Sales and Profit per Quarter.

14. What are the different types of connections that you can make with your dataset?

The different connections in Tableau are:

• File Systems such as .csv, Excel, etc.
• Relational Systems such as Oracle, SQL Server, DB2, etc.
• Cloud Systems such as Windows Azure, Google BigQuery, etc.
• Other Sources using ODBC.

15. What is the difference between Sets and Groups in Tableau?

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