Item: Tableau Desktop
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

Tableau Desktop is currently being used in my project. The most common implementation of Tableau is to create complex data visualizations to extract meaningful business insights, and thus it caters to all audiences. This helps us to create interactive dashboards with a sequence of visual graphics called stories. Recently we have also integrated Tableau with R and Python to easily map data insights to dashboards in real-time. Since Tableau can handle large amounts of data, complex statistical computations also help in providing dynamic variations to the dashboard.

Pros and Cons

It can handle very large amount of data
Drop-down options in dashboards allow users to analyze the impact of clusters within the dataset
It integrates well with Python and R

It is strictly a visualization tool, hence no data preprocessing is possible
Non-coding Tableau users will find it difficult to preprocess data using Python/R and then push the preprocessed data to Tableau
The reports generated has to be updated manually since Tableau does not allow automatic refreshes

Return on Investment

It has improved the business process outcomes
It has improved operational efficiencies
It has improved compliance and risk management

Alternatives Considered

Microsoft Power BI

We preferred Tableau over Power BI due to its user-friendly interface and interactive GUI. Since we work with large datasets, we observed that Power BI can deal with only a limited amount of data when compared to Tableau which creates complex visualizations in a time-efficient manner. Hence, as analysts we prefer Tableau.

Key Insights

Do you think Tableau Desktop delivers good value for the price?

Yes

Are you happy with Tableau Desktop's feature set?

Yes

Did Tableau Desktop live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Tableau Desktop go as expected?

Yes

Would you buy Tableau Desktop again?

Yes

Other Software Used

Anaconda, Microsoft SQL Server, Dataiku DSS, MongoDB, Blue Prism Intelligent RPA, Oracle Database, RStudio

Usability

From creating complex visualizations to generating stories, Tableau is the perfect tool for data analysts to consolidate meaningful data insights and present them to respective stakeholders. Integrating it with Python or R allows users to perform preprocessing steps and create visualizations using the drop-down options. Lastly, Tableau works very well with large datasets.

Support Rating

Tableau has a large customer support service, and all user queries are addressed very efficiently in very little time. Additionally, there are several Tableau-related blogs that provide solutions to almost all frequently generated issues. There are also several YouTube channels that teach Tableau from scratch, thereby providing a good foundation for new learners.

Likelihood to Recommend

Tableau Desktop is well-suited in projects where large datasets are used to gain business insights. A simple use-case for me is creating machine learning models and predicting outcomes and creating interactive dashboards using these predicted values and other accuracy metrics. The only limitation faced is preprocessing the data at an early stage (either in Python or R) and feeding this preprocessed data to Tableau.

Tableau Desktop for Data Analysts

Overall Satisfaction with Tableau Desktop