What is Tableau?
Harness the power of your data. Unleash the potential of your people. Choose the analytics platform that disrupted the world of business intelligence. Choose Tableau.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
89 Likeliness to Recommend
96 Plan to Renew
85 Satisfaction of Cost Relative to Value
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+90 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Tableau?
Pros
- Reliable
- Enables Productivity
- Performance Enhancing
- Helps Innovate
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Dashboard
Data Exploration and Visualization
Collaboration
Data Connectors and Data Mashup
Operational Reporting Capabilities
BI Platform Administration
Intelligent Alerts and Notifications
Self Service and Ad Hoc Capabilities
BI Security
Mobile
Vendor Capability Ratings
Business Value Created
Quality of Features
Breadth of Features
Ease of Data Integration
Ease of Implementation
Ease of Customization
Product Strategy and Rate of Improvement
Availability and Quality of Training
Ease of IT Administration
Usability and Intuitiveness
Vendor Support
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Tableau Reviews
- Role: Operations
- Industry: Other
- Involvement: End User of Application
Submitted Nov 2023
Easy to use. Wish it wouldn't take so long to load
Likeliness to Recommend
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
Shivam B.
- Role: Information Technology
- Industry: Insurance
- Involvement: IT Leader or Manager
Submitted Nov 2023
Tableau is a fantastic tool for visualisation
Likeliness to Recommend
What differentiates Tableau from other similar products?
Easier to use and better for visualisation
What is your favorite aspect of this product?
Visualisation is better
What do you dislike most about this product?
Cost and security
What recommendations would you give to someone considering this product?
Compare other tools
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
Cody N.
- Role: Operations
- Industry: Retail
- Involvement: End User of Application
Submitted Nov 2023
Incredible real-time data visualization
Likeliness to Recommend
What differentiates Tableau from other similar products?
Once a data dashboard is finished it's a game-changer. It makes data not just accessible but also remarkably easy to interpret. This aspect sets Tableau apart by providing users with a dynamic view. It's all there and easy to toggle to gain the view you want.
What is your favorite aspect of this product?
One of the standout features of Tableau is its capability to offer a near-real-time feed of data. This real-time functionality provides users with the most up-to-date insights. I've never seen a service handle such large data sets so seamlessly.
What do you dislike most about this product?
You need a team of dedicated data scientists to get the most out of Tableau. It would be nice if there were more learning resources to help train up the common user.
What recommendations would you give to someone considering this product?
If you have a data science team at your company it should be very easy to integrate. Just make sure you have the onsite technical knowledge required to really use it.