Tableau Interview Questions for Beginners
Tableau is a powerful visualization and business intelligence software application that enables users and other organizations to create shareable, interactive dashboards, reports, and data visualizations. It is widely used for data analysis and reporting purposes.
Tableau is a potent business intelligence (BI) and data visualization software program used to create interactive and shareable reports and dashboards. Users can connect to different data sources with it, transform unprocessed data into insightful visuals, and derive insights from their data. The user-friendly design of Tableau and its wealth of tools for data exploration, analysis, and storytelling are well-known.
To transform data into usable insights, make data-driven choices, and effectively convey findings through interactive reports and dashboards, it is widely utilized in businesses across industries. The several editions of Tableau include Tableau Desktop (for authoring reports), Tableau Server (for sharing and collaborating on reports), and Tableau Online (a cloud-based version).
Business Intelligence is a method that utilizes technology for data analysis and information delivery that aids leaders, managers, and employees in making strategic business decisions. As part of the BI process, organizations gather data from internal IT systems and external sources, prepare it for analysis, run queries against the data, create data visualizations, BI dashboards, and reports, and then make the analytics results accessible to business individuals for decision-making related to operations and strategic planning.
|
Basis |
Tableau |
Power BI |
|---|---|---|
| Provider | Tableau is an independent company that was later acquired by Salesforce. It operates independently but also has integrations with Salesforce products. | It is developed by Microsoft, Which is a component of the Microsoft business that easily interfaces with Microsoft products including SQL Server, Azure, and Excel. |
| Ease of Use | Although Tableau has a more difficult learning curve than Power BI, it offers more sophisticated customizations and analytical features. It is preferred by data analysts and experts. | Power BI, which is well known for its user-friendly interface, is frequently appreciated for its simplicity of use, which makes it available to a wider range of customers. |
| Data Connectivity | Tableau provides a wide range of data connectors and integration tools, making it suited for integrating with a variety of data sources, including databases, online services, and cloud platforms. | It provides a large choice of native connectors for connecting to different data sources, like as Excel, SQL servers, and cloud-based applications. Also, it supports unique data connectors. |
| Visualization | Tableau, which excels in complicated visuals, offers a wide range of customization options. Users who need extensive data exploration and visualization tend to favor it. | It provides customers with a wide range of visualization options and allows for the easy creation of interactive reports and dashboards. With regard to advanced analytics, it might have some restrictions. |
| Collaboration | It allows for sharing and collaboration via the Tableau server and Tableau online. It offers fine-grained control over user access and permissions. | Power BI Service enables collaboration and the sharing of reports and dashboards with coworkers and clients. It allows simple connectivity with Teams and Sharepoint. |
Different products of Tableau are :
- Tableau Desktop
- Tableau Server
- Tableau Online
- Tableau Public
- Tableau Prep
- Tableau Mobile
- Tableau Reader
- Tableau Prep Builder
Tableau supports 7 various different data types:
- String
- Numerical values
- Date and time values
- Boolean values
- Geographic values
- Date values
- Cluster Values
| Attributes | Dimension | Measure |
|---|---|---|
| Nature | They are categorical or qualitative data fields. They represent categories, labels, or attributes by which you can segment and group your data. | They are numerical or quantitative data fields. They represent quantities, amounts, or values that can be aggregated, or calculated. |
| Usage | They are used for grouping and segmenting data, creating hierarchies, and the structure for visualizations. | They are used for performing calculations and creating the numerical representation of the data as sum, average, etc. |
| Example | Category, Region, Product name, etc. | Sales(sum of sales), Profit(sum of profit), Quantity(sum of quantity), etc. |
Tableau uses several file extensions for different purposes within its ecosystem. Here are the most common file extensions used in Tableau and their significance:
- .twb (workbook): It represents a Tableau workbook, focusing on the layout and visualization details created in the Tableau desktop. It only contains the references to the location of the data source rather than the actual data itself. .twb files are smaller in size due to their lightweight nature. Receivers of .twb files must have access to the associated data source in order for the workbook to operate properly.
- .twbx (Packaged workbook): It is known as Tableau packaged workbooks and provides a comprehensive solution for sharing Tableau workbooks. They include both the actual data source and the workbook layout, including any custom calculations and visualizations. This embedded data ensures that recipients can open and view the workbook independently of the original data source. However, .twbx files tend to be larger due to the included data.
- .hyper (Data Extract File): To enhance the performance of the data in Tableau Workbooks, a Tableau Data Extract File (.hyper) is employed. For quicker querying and analysis, it maintains a snapshot of the data from the data source. When you import or export data from external sources, you may produce hyperfiles.
- .tds(tableau data source): It saves data source connections and schema information without data, facilitating consistent data source usage across multiple workbooks.
- .tdsx(packaged data source): It is a packaged version of a data source that includes a data source and associated extracts, ensuring comprehensive sharing.
- .tbm(Tableau Bookmark): It saves a snapshot of a single visualization within a workbook, allowing users to share specific insights or views.
- .twbx(Tableau Server Workbook): Optimized for server deployment, it is used for publishing Tableau workbooks to the Tableau server or Tableau online for web-based access.
- .tds(Tableau server Data source): Published data source files on Tableau serve or Tableau online for collaborative data analysis among users on the server.
With the help of Tableau, a potent business intelligence and data visualization tool, you can build engaging visualizations of a variety of data sources. Numerous data sources are supported by Tableau, such as:
- Databases:
Relational databases like MySQL, PostgreSQL, etc., NoSQL databases like MongoDB, etc., and Cloud-based databases such as Amazon Redshift, snowflake, etc. - Cloud Storage Services:
Amazon S3, Google Cloud Storage, and Azure Blob Storage - Web Connectors:
It provides different web connectors to connect to web-based APIs and services, allowing you to pull data from sources like Google Analytics, Salesforce, JSON, etc. - Statistical and Analytics software:
Integration with statistical tools like R and Python to execute advanced analytics and machine learning models. - Data Servers and OLAP cubes:
Connection to data servers and OLAP cubes, such as Microsoft Analytics Services(SSAS) and SAP HANA. - Excel and Text files:
You can directly connect to Microsoft Excel spreadsheets and text files(CSV, TSV) to import data.
In Tableau you can create different types of connections with your dataset:
- Live Connection: Real-time link to the data source for instant updates.
- Extract Connection(TDE): Snapshots of data for improved performance and scheduled refreshes.
- Blended Data Connection: Combine data from multiple sources in one visualization.
- Data source Union: Combine related tables or sheets within the same source.
- Cross-Database Join: Join tables from different databases or sources.
- Custom SQL Connection: Write custom SQL queries for data retrieval.
- Web Data Connector: Fetch data from web-based APIs.
- Local File Connection: Connect to local files(eg., Excel, CSV)
- Cloud Data Connection: Link to data in cloud-based services(e.g, AWS, GCS)
Tableau Interview Questions and Answers
Tableau is a powerful data visualization tool that turns raw data into understandable insights. It helps users create interactive and shareable dashboards, charts, and reports, making it easier to analyze and communicate complex data trends for better decision-making in business and other fields.
In this article, we have provided you with the top 50+ Tableau Interview questions with answers that cover everything from basics to advanced. Whether you are a fresher or an experienced IT professional (5 years or 10 years of experience ), this article gives you all the confidence you need to ace your next Tableau interview in one go!
Table of Content
- Tableau Interview Questions for Beginners
- Intermediate Tableau Interview Questions
- Tableau Interview Questions for Experienced
- Scenario Based Tableau Interview Questions