Tableau offers five main products:
Tableau Desktop 2019.4 (as of November 6, 2019)
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.
Whether our data is in an on-premise database, a database, a data warehouse, a cloud application, or in an Excel file, we can analyze it with Tableau. We can create views of our data and share it with colleagues, customers, and partners. We can use Tableau to blend it with other data, and we can keep our data up to date automatically.
A Filter restricts unnecessary data; it shows the exact data we want. Basically, Filters are of three types:
Suppose, we have data like below:
Eid Ename Salary Dept
1.abc 2000 java
2.bbc 3000 .net
3.Krishna 2500 java
5.Vamshi 3000 mainframes
1.abc 1000 testing
2.bbc 3000 tableau
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 column and salary on rows, and we will get the sum (salary) of each and individual employee Now, change the measure type as Avg
Choose salary option: choose measure types as ‘Avg’
Disaggregation: To display each and every transaction
When we 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, we want to see the individual salary transactions for each employee. We can create a view like that by selecting Analysis > Aggregate Measures.
Right-click on Filter > Customize > uncheck the Show All option
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Yes! For example, in a data source, if we have columns like EmpID, EmpName, EmpDept, EmpDsignation, EmpSalary, and in reports we are using EmpName on columns and EmpSalary on rows, we can use EmpDesignation on Filters.
Extract can be used anywhere without any connection, and we can build our own visualizations without connecting to a database.
Suppose, we have five different Excel files (2007.xls, 2008.xls, … 2011.xls) with the same fields (film name, genre, budget, rating, profitability, etc.) but with data of different years (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?
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We can join a maximum of 32 tables; it is not possible to combine more than 32 tables.
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Joins in Tableau
Suppose, our client is in the 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, etc. Now, the client wants to know the customer-wise claims and the customer-wise rejected claims table using the Joins. Join is a query that combines the data from two or more tables by making use of the Join condition.
In Tableau, Joins can be performed in two ways:
If we create Joins on the fields, in Tableau, all the table names are suffixed with $. While performing Joins on multiple tables, always go with the less amount of data tables, so that we can improve the performance.
In Tableau, Joins are divided into two types:
In the Join condition, if we are using equality (‘=’) operator, then such a kind of join is called Equi Join. Equi Join is further divided into three types:
Tableaa.id = Tableb.id
Table A full outer join Table B ON tablea.id= tableb.id
In the Join condition, if we are using operators apart from the equality (‘=’) operator (such as, <, >, <=, >=, and =!), then such a kind of Join is called Non-equi Join.
Data Blending in Tableau
Consider the same client. Suppose, they are operating their services in Asia, Europe, NA, and so on, and they are maintaining Asia data in SQL, Europe data in SQL Server, and NA data in MySQL.
Now, our client wants to analyze their business across the world in a single worksheet. In this case, we can’t perform a Join. Here, we have to make use of the data blending concept.
Normally, in Tableau, we can perform the analysis on a single data server. If we want to perform the analysis of data from multiple data sources in a single sheet, then we have to make use of this new concept called data blending.
Data blending mixes the data from different data sources and allows users to perform the analysis in a single sheet. ‘Blending’ means ‘mixing’ and when we are mixing the data sources, then it is called data blending.
Rules to Perform Data Blending
In order to perform data blending, there are a few rules:
In Tableau, we can perform data blending in two ways.
Data Blending Functionality
Yes, we can do it, but for better performance we have to use Extract.
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The file extension .twb is a live connection; it points to the data source. The user receiving .twb needs permission to access the said data source and no data is included.
On the other hand, .twbx takes the data offline and stores it as a package or zip-like file, thereby eradicating the need for permissions.
To display two measures in one graph, Tableau uses dual axes.
Related Article: How To Use Tab admin For Administrative Task Automation In Tableau?
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Here, multiple measures are shown in a single axis and all the marks are shown in a single pane.
Tableau stands out for several reasons:
We can’t perform testing in Tableau. It is a data visualization software.
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Tableau currently does not support the multi-valued parameters. Case Study: The “dynamic parameter with a blend” technique can be used to highlight a single value, but not multiple values because of the way it works. As Tableau parameters are not dynamic, we cannot “filter” the list of values at runtime.
We can use parameters with filters, calculated fields, actions, measure-swaps, changing views, and auto-updates.
Custom SQL query is written after connecting to data for pulling the data in a structured view. For example, suppose, we have 50 columns in a table, but we need just 10 columns only. So instead of taking 50 columns, we can write a SQL query. The performance will increase.
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Tableau provides easy to use, best in class, visual analytic capabilities, but it does not help with plumbing (data foundation). We could, for example, marry SQL Server with Tableau to get the complete package. Tableau licenses are relatively expensive if we are looking to scale.
Traditional BI can handle it all but with significant upfront costs, higher consulting, hardware, and software costs. Among the mega-vendors, only Microsoft can provide a reasonable value proposition. Open-source vendors like Pentaho and Jaspersoft do not have an abundant-enough talent pool, yet.
Palantir and Tableau are very different. Palantir has its roots in large data computer science problems involving security, payments, fraud detection, and the like. Its customers/investors include PayPal, CIA, and others.
Tableau is a visualization player, with roots in Stanford University Research. Its Visual Query Language (VizQL) allows users to build visualizations on top of the standard data warehouses or spreadsheets.
Here, say, we have Filter1 and Filter2. Based on Filter1, we need to use Filter2 on the data. For example, consider Filter1 as ‘Country’ and Filter2 as ‘States.’
Let’s choose Country as ‘India’ and hence Filter2 should display only the states of India.
Choose options of Filter2 states: select option of ‘Only relevant values’
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Yes, for sure! It gives us data insights much more than the others. It helps us plan and point the anomalies and improvise our process for betterment.
Using filters or calculated fields, we can display the top five and the last 5 sales in the same view.
If we want to show the sales and profit of each and every city under the states in the same worksheet, first, we should have State, City, Sales, and Profit fields in our dataset.
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Documents » My Table Repository » Preferences.tps
Note: In Tableau 9.0, we have a color picker option.
Tableau’s major goal is to help people see and understand data. Its software products put the power of data into the hands of everyday people, allowing a broad population of business users to engage with their data, ask questions, solve problems, and create values.
Related Article: Learning To Leverage Tabcmd In Tableau
Tableau Public is a free service that lets anyone publish interactive data to the web. Once on the web, anyone can interact with the data, download it, or create their own visualizations for it. No programming skills are required here. We can also check out the gallery to see some of the things people have been doing with it.
Data modeling is the analysis of data objects that are used in a business or other context and the identification of the relationships among these data objects. Data modeling is the first step in performing object-oriented programming.
I think we all work on different projects using Tableau, so the work begins from understanding the requirement, and then we have to get the required data, create a storyboard, create visualizations in Tableau, and then present it to the client for review.
Parameters are dynamic values that can replace constant values in calculations, and they can serve as filters.
Tableau’s performance is based on the performance of the data source. If the data source takes more time to execute a query, then Tableau must wait up to that time.
Tableau Desktop Log files are located in C:UsersMyDocumentsMy Tableau Repository. If we have a live connection to the data source, we need to check the log.txt and tabprotosrv.txt files. If we are using Extract, have to check the tdeserver.txt file. The tabprotosrv.txt file often shows detailed information about queries.
Related Article: What Kinds Of Tasks Can Be Done With Tabcmd In Tableau?
Page shelf is a powerful part of Tableau that we can use to control the display of the output and the printed results of the output.
Yes, it may have its own drop-down list. The entries we make in the Parameter while creating it can be viewed as items in the drop-down list.
After the creation of dashboards, if we get a problem from the SQL side it means Custom SQL….How to Rectify the SQL performance from custom SQL.
Data blending is the combining of data from two or more different sources. We can combine the data between two sources, such as Oracle, SQL Server, Excel, and others.
Consider the admission data given in a relational database and the admission target data given in an Excel spreadsheet. Now, to compare the actual admissions with the target admissions, we can perform data blending. Here, we will blend the data based on some common dimensions of both sources to access the measure of the Admissions target. We list the two sources involved in data blending as the primary and secondary sources of the data. A left join is performed between the primary data source and the secondary data source, wherein all the data rows from the primary data source and only the matching data rows from the secondary data source are fetched.
Each data source in data blending includes its own collection of dimensions and measures. Data blending is useful when combining data from a variety of sources.
Data joining, on the other hand, is also combining data but from two or more tables or sheets within the same data source.
Combining two tables from the same SQL Server or Oracle Database or DB2 or any other data source. Combining two worksheets or more in the same Excel package will also fall under data joining.
Data joining is useful when combining data from a single source with several tables, sheets, or others.
Yes, it is possible.
Yet, this question doesn’t have a straight answer since we can store massive amounts of data differently on the basis of the different configurations of Tableau Server implementation (such as 8 cores, 16 cores, etc.). Not just if Hyper is used or not, but other factors like server memory may also affect the amount of the data we can store.
Note: When dumping large amounts of data on Tableau Server, we have to make sure that this data volume should not affect the dashboard’s performance and the response time, and also, the processing time for extracts. This is where Tableau’s efficiency is enhanced by Hyper.
Traditional BI solutions are powerful and can provide scaling and reliability. Various well-established software firms have endorsed them. These solutions provide ample security for data. Although, they need good BI technical knowledge and skills to work with them. Oracle BI and Qlikview are just two simple tools used among them.
Tableau is one of the top BI tools used in the industry today, providing easy operation and understanding without much knowledge of BI competencies. It has simple drag-and-drop functionality and a smart way to categorize the fields of data. However, in Tableau Public, data security is not provided, while in the Professional version, security is enabled.
RANK and INDEX come under table calculations in Tableau. INDEX mainly deals with a record’s physical position. Incremental numbers are assigned according to the record’s physical order. Whereas, RANK deals with a record’s value. The highest value gets the highest rank and the lowest value gets the lowest rank.
We will see the option to schedule reports when uploading a report on Tableau Server. We can click on this button to set the time to refresh the data.
If our server license expires today, our user name on the server will have the role ‘unlicensed’ which means that we cannot access but others can. The Site Admin can ‘Change Ownership’ to another person, so Extracts if enabled do not fail.
Here is how we can refresh the dashboard in every 3 seconds:
Related Article: What Are The Rapid-fire Analysis At A Public Utility In Tableau?
Tableau Desktop is based on breakthrough technology from Stanford University that lets us drag and drop to analyze data. It is a great data visualization tool, with which we can connect to data in a few clicks, then visualize and create interactive dashboards with a few more clicks.
We can talk about the features and functionalities of them for days, but at a high level, there are four major differences:
Related Article: Aggregating Disparate Data Sources At A Large University In Tableau
Tableau is the Business Intelligence software that allows anyone to easily connect to data and then visualize and create interactive and sharable dashboards. It’s easy enough that any Excel user can learn it, but powerful enough to satisfy even the most complex analytical problems. With tableau, securely sharing the findings with others only takes seconds.
Tableau Server is a browser- and mobile-based insight anyone can use. We can easily publish dashboards with Tableau Desktop and share them throughout our organization. It’s easy to set up and even easier to run.
R is a popular open-source environment for statistical analysis. Tableau Desktop can now connect to R through calculated fields and take advantage of R functions, libraries, and packages, and even the saved models. These calculations dynamically invoke the R engine and pass values to R via the Rserve package and they are returned to Tableau.
Quick filter is used to view the filtering options and can be used to select options. Whereas, the Normal filer is something with which we can limit the options from the list or use some conditions to limit the data by field or value.
Thank you so much! It should be incredibly useful for job interviews. Keep it up.
Thanks for sharing the nice collection of Tableau interview questions.
Nice collection..Helps me a lot
thank you so much sharing these interview questions .i need so more real time interview questions
Good one thx for sharing
Good Collection- Very helpful from a fresher pov and good brush for experienced pov
Thanks for sharing the knowledge. I am impressed with your way of explanation in this Tableau Interview Questions and answers.
Thanks a lot for the Interview questions and answers. It was very helpful to me. when i have attended the interview for Tableau Developer.
Well written and explained details about Tableau.
Thanks a ton! The features explained as available in Tableau certainly helps to do a comparison against other visualisation tools such as SAS Visual Analytics
Great work..!! Thanks for sharing.
Thank u, Sharing is a good habit that u done it.
Sharing is a good habit that u have done it. Thank u.
It is good, thanks for sharing…
Thanks for sharing tableau interview questions
Great work!! Thanks for sharing tableau Q & A.
Please include topic on confidence bands calculation for linear trendlines in Tableau?
Great post! Answers are to the point
Thanks for sharing
Can we use group and sets in calculation field in tableau?
“Groups – Combine dimension members into higher level categories. Groups can not be used on Calculated Fields. Sets – Create a custom field based on existing dimensions that can be used to encode the view with multiple dimension members across varying dimension levels. “
Good info !!! Very helpful.
I would like to see more of such interesting questions
Hi Intellipaat, great post. I am takeing up tableau certification exam, can you please share more of related the questions with me? My id- [email protected]
Thanks for this post, one of my friend preparing for his Tableau Interview. I will share these Interview questions with him
Nice post, why don’t you include implement a serialization also.
Sure, thanks for you suggestion , we will defenitely work on it
HI thank you for your valuble information.i have an doubt can any one expalin please what is the procese of drilling on tableau dashboard
1. first we have to create group from ‘category’ field select ‘furniture’ and ‘Office’ one group and remaining fields name is ‘other’ 2. drag to category field in columns and as well as group name also 3. calculated field is ‘[Category (group)] = [Category]’ 4. click ‘ok’
Please update answer for question number 13
Thanks a lot for sharing valuable info about tableau interview Q&A for interview preparation..Can you please add up real-time scenario based Q&A and practical case study as well..
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