BigData / Tableau Interview Questions

Tableau is a visual analytics platform transforming the way we use data to solve problems-empowering people and organizations to make the most of their data.

Tableau allows users to connect to various data sources, create interactive dashboards, and generate insightful reports. Tableau is the Business Intelligence (BI) industry's most potent and fastest tool for visualizing data. It turns the raw data into a format that is easy to understand. Data visualization or diagrams make it easy for employees at all levels of an organization to understand the information.

Data visualization is a way to represent data that is visually appealing and interactive. With advancements in technology, the number of business intelligence tools has increased which helps users understand data, data sets, data points, charts, graphs, and focus on its impact rather than understanding the tool itself.

Tableau offers a myriad of data sources such as local text files, MS Excel, PDFs, JSON or databases and servers like Tableau Server, MySQL Server, Microsoft SQL Server, etc. Categorically, there are two types of data sources that you can connect to in Tableau; To a file and To a server.

Tableau supports the following 7 data-types:

• String values,
• Number/Integer values,
• Date values,
• Date & Time values,
• Boolean values,
• Geographic values,
• and Cluster or mixed values.

Measures are the numeric metrics or measurable quantities of the data, which can be analyzed by dimension table. Measures are stored in a table that contain foreign keys referring uniquely to the associated dimension tables. The table supports data storage at atomic level and thus, allows more number of records to be inserted at one time. For instance, a Sales table can have product key, customer key, promotion key, items sold, referring to a specific event.

Dimensions are the descriptive attribute values for multiple dimensions of each attribute, defining multiple characteristics. A dimension table ,having reference of a product key form the table, can consist of product name, product type, size, color, description, etc.

Visualize Data: Rather than having complex computations over an Excel sheet, Tableau provides beautiful insights, data blending, and dashboarding derived from the data.

Create interactive visualizations: Tableau provides a drag-n-drop facility to quickly let the users interact with the data. You can check some of the templates created using Tableau in the Tableau gallery.

With Tableau's gallery of templates, you can choose your option and customize it. With data visualization features, you can easily embed tons of information in the form of infographics that appeal to the audience.

Easy implementation: With drag-and-drop options, Tableau is reportedly easier to use. This is one such tool that you can learn without having any coding background or experience in Python, Business objects, or DOMO.

Handle large amounts of data: Tableau is competent enough to handle millions of rows without affecting the dashboard performance.

Integration with scripting languages: With Tableau, you can perform complex data computations using scripting languages like Python and R by importing some visuals or packages.

The parameters in Tableau are the workbook variables like a number, date, or calculated field that allows users to replace a constant value in a calculation, filter, or reference line.

For example, you create a field that returns true if the sales are greater than 30,000 and false if otherwise. Parameters are used to replace these numbers (30000 in this case) to dynamically set this during calculations. Parameters allow you to dynamically modify values in a calculation. The parameters can accept values in the following options:

• All: Simple text field.
• List: List of possible values to select from.
• Range: Select values from a specified range.