Tableau Desktop is a data visualization product from Tableau. It connects to a variety of data sources for combining disparate data sources without coding. It provides tools for discovering patterns and insights, data calculations, forecasts, and statistical summaries and visual storytelling.
$75
per month per user
Trendpop
Score 7.0 out of 10
N/A
N/A
N/A
Pricing
Tableau Desktop
Trendpop
Editions & Modules
Tableau
$75
per month per user
Tableau Enterprise
$115
per month per user
No answers on this topic
Offerings
Pricing Offerings
Tableau Desktop
Trendpop
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
All pricing plans are billed annually.
—
More Pricing Information
Community Pulse
Tableau Desktop
Trendpop
Features
Tableau Desktop
Trendpop
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Tableau Desktop
8.3
Ratings
2% above category average
Trendpop
-
Ratings
Pixel Perfect reports
8.80 Ratings
00 Ratings
Customizable dashboards
8.40 Ratings
00 Ratings
Report Formatting Templates
7.80 Ratings
00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Tableau Desktop
8.7
Ratings
8% above category average
Trendpop
-
Ratings
Drill-down analysis
8.60 Ratings
00 Ratings
Formatting capabilities
9.20 Ratings
00 Ratings
Integration with R or other statistical packages
7.70 Ratings
00 Ratings
Report sharing and collaboration
9.20 Ratings
00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Tableau Desktop
8.1
Ratings
2% below category average
Trendpop
-
Ratings
Publish to Web
7.40 Ratings
00 Ratings
Publish to PDF
7.90 Ratings
00 Ratings
Report Versioning
8.20 Ratings
00 Ratings
Report Delivery Scheduling
9.20 Ratings
00 Ratings
Delivery to Remote Servers
8.00 Ratings
00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).
The Visualizations graphics are really good and the color options help in designing attractive charts. They help to convey more information and can be made interactive.
You can add filters with offer you to plug and play with values and understand different outcomes.
You can drag and drop options while creating charts and dashboards. also it is a very fluid layout.
Because right now its the best option out there (disclosure: I haven't used Qlikview or some of the other direct competitors of Tableau). The big investment is in Tableau Server not desktop. For the cost of the license of Tableau desktop, its a pretty good deal. You can hook it up to pretty much any data source easily. You can easily share the visualizations with your team/colleagues easily. Tableau Desktop is generally easy to use for business users. But the more advanced stuff is better suited for a analyst or someone with a IT/CS background.
Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.
When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.
Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast
The Tableau Desktop's support team has been very helpful and tend to response very quickly. After all you have paid very premium price for the product and it goes to the services. This makes using the tool much easier for these who doesn't have such experience to get help quickly.
It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.
I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems
Time needs to be spent ahead of implementation to make sure data sources are set up and ready. Consultants need to understand the data sources and the goals before setting foot on-site. Installation is easy, learning to use it takes time. The training resources available are great.
Tableau Desktop is clearly one of the best in the business. It has incredible capabilities, and many features are extremely useful. The intuitiveness of the dashboards and the graphical nature of the visualizations are widely used features and super helpful. One of the other benefits is that both programmers and non-programmers can equally explore and create their own opportunities, and seamless integration is possible.
Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.