If you're looking for Tableau Interview Questions for Experienced or Freshers, you are at right place. There are lot of opportunities from many reputed companies in the world. According to research Tableau has a market share of about 16.2%. So, You still have opportunity to move ahead in your career in Tableau Analytics. Mindmajix offers Advanced Tableau Interview Questions 2018 that helps you in cracking your interview & acquire dream career as Tableau Developer.
Tableau Real Time Interview Questions:
Q. What is the difference between context filter to other filters?
Whenever we crate context filter
- Tableau will create a temporary table for this particular filter set and other filters will be apply on context filter data like cascade parameters… suppose we have crated context filter on countries >> we have chosen country as USA and India
- Tableau will create a temporary table for this two countries data and if you have any other filers >>other will be apply on this two countries data if we don’t have any context filter
- Each and individual record will check for all filters
Q. What is disadvantage of context filters?
- The context filter is not frequently changed by the user – if the filter is changed the database must recomputed and rewrite the temporary table, slowing performance.
- When you set a dimension to context, Tableau crates a temporary table that will require a reload each time the view is initiated. For Excel, Access and text data sources, the temporary table created is in an Access table format. For SQL Server, My SQL and Oracle data sources, you must have permission to create a temporary table on your server. For multidimensional data source, or cubes, temporary tables are not crated, and context filters only defined which filters are independent and dependent.
Q. What are the five main product offered by Tableau company?
Tableau offers five main products: Tableau Desktop, Tableau Server, Tableau Online, Tableau reader and Tableau Public.
Tableau offers five main products: Tableau Desktop, Tableau Server, Tableau Online, Tableau reader and Tableau Public.
Q. What is the current latest version of Tableau Desktop(as of Sep, 25th 2017)?
Current version: Tableau Desktop Version 10.4
Q. What is data visualization?
Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g. points, lines or bars) contained in graphics.
Data visualization refers to the techniques used to communicate data or information by encoding it as visual objects (e.g. points, lines or bars) contained in graphics.
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Q. Why tableau?
Whether your data is in an on-premise database, a database, a data warehouse, a cloud application or an Excel file, you can analyze it with Tableau. You can create views of your data and share it with colleagues, customers, and partners. You can use Tableau to blend it with other data. And you can keep your data up to date automatically.
Whether your data is in an on-premise database, a database, a data warehouse, a cloud application or an Excel file, you can analyze it with Tableau. You can create views of your data and share it with colleagues, customers, and partners. You can use Tableau to blend it with other data. And you can keep your data up to date automatically.
Q. What are Filters? How many types of filters are there in Tableau?
Filter is nothing but it is restricted to unnecessary, it is showing exact data. Basically filters are 3 types.
1. Quick filter
2. Context filter
3. Datasource filter
Filter is nothing but it is restricted to unnecessary, it is showing exact data. Basically filters are 3 types.
1. Quick filter
2. Context filter
3. Datasource filter
Q. What is disaggregation and aggregation of data?
Suppose I have data like
Eid Ename Salary Dept
1.abc 2000 java
2.bbc 3000 .net
3.Krishna 2500 java
Madhu 300
5.Vamshi 3000 mainframes
1.abc 1000 testing
2.bbc 3000 tableau
3.krishna 5000.net
4.Madhu 7000 testing
vanshi 9000 tableau
1 abc 11000 Mainframes
2 bbc 13000testing
3 krishna 15000 java
4 Madhu 17000 .nte
5 vamshi 19000.net
Aggregation: to display aggregate data
Sum/avg salary by each individual employee
drag ename on columna and salary on rows we will get sum (salary) of each and individual employee
now change measure type as Avg
Choose salary option – choose measure types as “Avg”
Disaggregation: To display each and every transaction
When you look at the aggregated data in the views above, each bar represents all transactions for a specific employee summed up or averaged into a single value. Now say that you want to see the individual salary transactions for each employee. You can create a view like that by selecting Analysis>Aggregate Measures.
Suppose I have data like
Eid Ename Salary Dept
1.abc 2000 java
2.bbc 3000 .net
3.Krishna 2500 java
Madhu 300
5.Vamshi 3000 mainframes
1.abc 1000 testing
2.bbc 3000 tableau
3.krishna 5000.net
4.Madhu 7000 testing
vanshi 9000 tableau
1 abc 11000 Mainframes
2 bbc 13000testing
3 krishna 15000 java
4 Madhu 17000 .nte
5 vamshi 19000.net
Aggregation: to display aggregate data
Sum/avg salary by each individual employee
drag ename on columna and salary on rows we will get sum (salary) of each and individual employee
now change measure type as Avg
Choose salary option – choose measure types as “Avg”
Disaggregation: To display each and every transaction
When you look at the aggregated data in the views above, each bar represents all transactions for a specific employee summed up or averaged into a single value. Now say that you want to see the individual salary transactions for each employee. You can create a view like that by selecting Analysis>Aggregate Measures.
Q. How to remove the All options from a Tableau auto – filter?
Right click filter>>customize>>uncheck show all option
Right click filter>>customize>>uncheck show all option
Q. Can we use non – used columns (Columns which are not used in reports but data source has columns) in Tableau Filters?
Yes!
Ex. In data source I have column like
empID, EmpName, EmpDept,EmpDsignation, EmpSalary
In reports I am using empname on columns and empsalry on rows.
I can use empDesignation on Filters
Yes!
Ex. In data source I have column like
empID, EmpName, EmpDept,EmpDsignation, EmpSalary
In reports I am using empname on columns and empsalry on rows.
I can use empDesignation on Filters
Q. What is benefit of Tableau extract file over the live connection?
Extract can be used anywhere without any connection and you can build your own visualizations without connecting to Database.
Extract can be used anywhere without any connection and you can build your own visualizations without connecting to Database.
Q. How to combine two excel files with same fields but different data (different years)?
I have 5 different excel files (2007.xls, 2008.xls..2011.xls) with same fields (film name, genre, budge, rating, profitability) but with data from different year (2007 to 2011). Can someone tell me how can I combine the film name, genre and profitability so that I can see the visualization of 2007 to 2011 in a single chart?
I have 5 different excel files (2007.xls, 2008.xls..2011.xls) with same fields (film name, genre, budge, rating, profitability) but with data from different year (2007 to 2011). Can someone tell me how can I combine the film name, genre and profitability so that I can see the visualization of 2007 to 2011 in a single chart?
Related Article: Employing Visual Analytics To Aid Succession Planning In Tableau
Q. Max no of tables we can join in Tableau?
We can join max 32 table, it’s not possible to combine more than 32 tables.
We can join max 32 table, it’s not possible to combine more than 32 tables.
Q. What is the difference between joining and blending in Tableau?
Joins in Tableau:
For Eg: your client is in Healthcare domain and using SQL Server as their database. In SQL server there may be many Tableau like Claims Tables, Rejected Claims Table, Customer Table. Now, client wants to know customer wise claims and customer wise rejected claims table using the joins. Join is a query that combines the data form 2 or more tables by making use of Join condition.
We can join max 32 table, it’s not possible to combine more then 32 tables.
In Tableau the joins can perform in 2 ways.
1. By making use of common columns.
2. By making use of common data types.
If we create joins on the fields in Tableau all the table names are suffixing with $. While performing the joins on multiple tables, always go with the les amount of data tables, so that we can improve the performance.
In Tableau the joins are divided into 2 types.
1.Equi Join,
2.Non Equi Join
1. Equi Join: in the join condition if we are using Equality”=”operator then such a kind of join called as Equi join.
2. Non Equi Join: in the join condition apart from the Equality”=”if we use any other operator like <,>,<=,>= and=! Then such a kind of joins are called as Non Equi Join
Equi Join is divided into 3 types
1. Inner Join,
2. Outer Join,
3. Self – Join.
1.Inner Join: Inner join will loads the only matching records from the both tables. Inner join condition:
Tableaa.id = Tableb.id
2.Outer Join:
Again the outer join divided into 3 types.
a)Left Outer Join,
b)Right Outer Join,
c)Full Outer Join.
Joins in Tableau:
For Eg: your client is in Healthcare domain and using SQL Server as their database. In SQL server there may be many Tableau like Claims Tables, Rejected Claims Table, Customer Table. Now, client wants to know customer wise claims and customer wise rejected claims table using the joins. Join is a query that combines the data form 2 or more tables by making use of Join condition.
We can join max 32 table, it’s not possible to combine more then 32 tables.
In Tableau the joins can perform in 2 ways.
1. By making use of common columns.
2. By making use of common data types.
If we create joins on the fields in Tableau all the table names are suffixing with $. While performing the joins on multiple tables, always go with the les amount of data tables, so that we can improve the performance.
In Tableau the joins are divided into 2 types.
1.Equi Join,
2.Non Equi Join
1. Equi Join: in the join condition if we are using Equality”=”operator then such a kind of join called as Equi join.
2. Non Equi Join: in the join condition apart from the Equality”=”if we use any other operator like <,>,<=,>= and=! Then such a kind of joins are called as Non Equi Join
Equi Join is divided into 3 types
1. Inner Join,
2. Outer Join,
3. Self – Join.
1.Inner Join: Inner join will loads the only matching records from the both tables. Inner join condition:
Tableaa.id = Tableb.id
2.Outer Join:
Again the outer join divided into 3 types.
a)Left Outer Join,
b)Right Outer Join,
c)Full Outer Join.
- Left outer join: Displays the complete data from the left + matching records from the right table.
Condition:
tablea.id(+)- Right Outer Join: displays the complete data from the right + matching records from the left.
Condition:
tablea.id(+)=tableb.id- Full outer join: full outer join load the complete data from the left table and right table. Condition: Table A full outer join Table B ON
tablea.id= tableb.id
3.Self-Join: if we are performing join to the same table itself such a kind of join called as self-join
Non Equi Join:
In the join condition if we are using the operators apart from the equality “=” then such a kind of joins are called as Non Equi join.
Data Blending in Tableau:
For ex: your client is same Healthcare Client. They are operating their services in Asia, Europe, NA and so on & the are maintaining Asia data in SQL, Europe Data in SQL Server and NA data in MY SQL.
Now, your client wants to analyze their business across the world in a single worksheet. So you can’t perform join here.
Now you have make use of Data Blending Concept.
Normally in the Tableau we can perform the analysis on the single data server. If we want to perform the analysis from the multiple data sources in a single sheet then we have to make use of a new concept called as data blending.
Data blending mix the data from the different data sources and allow the users to perform th analysis in a single sheet. Blending means mixing. If we are mixing the data sources then it is called as data blending.
Rules to perform the data blending
In order to perform data blending there are few rules.
1. If we are performing the data blending on 2 data source these 2 data sources should have at least 1 common dimension.
2. In that common dimension at least 1 value should match.
In Tableau we can perform the data blending in 2 ways.
1. Automatic way
2. Custom way
1. Automatic way: In the automatic way Tableau automatically defines the relationship between the 2 data sources based on the common dimensions and based on the matching values and the relationship is indicated with Orange color.
2. Custom or Manual way: In the manual or custom way the user need to define the relationship manually.
Data blending fuctionality
1. All the primary data sources and the secondary data sources are linked by specific relationship
2. while performing the data blending each work sheet has a primary connection and optionally it might contains several secondary connections.
3. All the primary connections are indicated in the Blue in the work sheet and all the secondary data sources indicated with the Orange color tick mark.
4. In the data blending 1 sheet contains 1 primary data source and 1 sheet can contain end number of secondary data sources.
Non Equi Join:
In the join condition if we are using the operators apart from the equality “=” then such a kind of joins are called as Non Equi join.
Data Blending in Tableau:
For ex: your client is same Healthcare Client. They are operating their services in Asia, Europe, NA and so on & the are maintaining Asia data in SQL, Europe Data in SQL Server and NA data in MY SQL.
Now, your client wants to analyze their business across the world in a single worksheet. So you can’t perform join here.
Now you have make use of Data Blending Concept.
Normally in the Tableau we can perform the analysis on the single data server. If we want to perform the analysis from the multiple data sources in a single sheet then we have to make use of a new concept called as data blending.
Data blending mix the data from the different data sources and allow the users to perform th analysis in a single sheet. Blending means mixing. If we are mixing the data sources then it is called as data blending.
Rules to perform the data blending
In order to perform data blending there are few rules.
1. If we are performing the data blending on 2 data source these 2 data sources should have at least 1 common dimension.
2. In that common dimension at least 1 value should match.
In Tableau we can perform the data blending in 2 ways.
1. Automatic way
2. Custom way
1. Automatic way: In the automatic way Tableau automatically defines the relationship between the 2 data sources based on the common dimensions and based on the matching values and the relationship is indicated with Orange color.
2. Custom or Manual way: In the manual or custom way the user need to define the relationship manually.
Data blending fuctionality
1. All the primary data sources and the secondary data sources are linked by specific relationship
2. while performing the data blending each work sheet has a primary connection and optionally it might contains several secondary connections.
3. All the primary connections are indicated in the Blue in the work sheet and all the secondary data sources indicated with the Orange color tick mark.
4. In the data blending 1 sheet contains 1 primary data source and 1 sheet can contain end number of secondary data sources.
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