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103 Ratings

Tableau Desktop

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103 Ratings
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Score 8.5 out of 101

Tableau Desktop

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Top Rated
1270 Ratings
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Score 8.2 out of 101

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Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
Thomas Young profile photo

Tableau Desktop

With Tableau, you can create an infinite number of tables, of greater or lesser complexity, and be able to discover and analyze information with very visual graphics. You can use unlimited amounts of data, it is an ideal solution for companies and organizations. The additional information for the users is not totally private, it can be viewed by other users, although there is the modality of granting a permission to access. The files used for graphics must always be updated and must have access to the Internet to access the tool
Maria Gabriela Hernandez profile photo

Feature Rating Comparison

BI Standard Reporting

Apache Spark
Tableau Desktop
8.4
Pixel Perfect reports
Apache Spark
Tableau Desktop
8.4
Customizable dashboards
Apache Spark
Tableau Desktop
8.8
Report Formatting Templates
Apache Spark
Tableau Desktop
8.1

Ad-hoc Reporting

Apache Spark
Tableau Desktop
8.3
Drill-down analysis
Apache Spark
Tableau Desktop
8.5
Formatting capabilities
Apache Spark
Tableau Desktop
8.2
Integration with R or other statistical packages
Apache Spark
Tableau Desktop
8.0
Report sharing and collaboration
Apache Spark
Tableau Desktop
8.5

Report Output and Scheduling

Apache Spark
Tableau Desktop
7.7
Publish to Web
Apache Spark
Tableau Desktop
8.3
Publish to PDF
Apache Spark
Tableau Desktop
8.2
Report Versioning
Apache Spark
Tableau Desktop
7.3
Report Delivery Scheduling
Apache Spark
Tableau Desktop
7.5
Delivery to Remote Servers
Apache Spark
Tableau Desktop
7.3

Data Discovery and Visualization

Apache Spark
Tableau Desktop
8.0
Pre-built visualization formats (heatmaps, scatter plots etc.)
Apache Spark
Tableau Desktop
8.6
Location Analytics / Geographic Visualization
Apache Spark
Tableau Desktop
8.8
Predictive Analytics
Apache Spark
Tableau Desktop
6.8

Access Control and Security

Apache Spark
Tableau Desktop
7.6
Multi-User Support (named login)
Apache Spark
Tableau Desktop
8.1
Role-Based Security Model
Apache Spark
Tableau Desktop
7.3
Multiple Access Permission Levels (Create, Read, Delete)
Apache Spark
Tableau Desktop
7.6
Single Sign-On (SSO)
Apache Spark
Tableau Desktop
7.2

Mobile Capabilities

Apache Spark
Tableau Desktop
7.6
Responsive Design for Web Access
Apache Spark
Tableau Desktop
8.2
Dedicated iOS Application
Apache Spark
Tableau Desktop
7.2
Dedicated Android Application
Apache Spark
Tableau Desktop
6.9
Dashboard / Report / Visualization Interactivity on Mobile
Apache Spark
Tableau Desktop
8.2

Application Program Interfaces (APIs) / Embedding

Apache Spark
Tableau Desktop
7.1
REST API
Apache Spark
Tableau Desktop
8.0
Javascript API
Apache Spark
Tableau Desktop
7.0
iFrames
Apache Spark
Tableau Desktop
6.7
Java API
Apache Spark
Tableau Desktop
6.9
Themeable User Interface (UI)
Apache Spark
Tableau Desktop
7.0
Customizable Platform (Open Source)
Apache Spark
Tableau Desktop
7.0

Pros

  • Ease of use, the Spark API allows for minimal boilerplate and can be written in a variety of languages including Python, Scala, and Java.
  • Performance, for most applications we have found that jobs are more performant running via Spark than other distributed processing technologies like Map-Reduce, Hive, and Pig.
  • Flexibility, the frameworks comes with support for streaming, batch processing, sql queries, machine learning, etc. It can be used in a variety of applications without needing to integrate a lot of other distributed processing technologies.
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  • With Tableau, you can easily analyze information, interact, filter, drill down and graph data
  • Tableau allows you to work with multiple data sources, allowing you to convert them into visualized information in easy-to-analyze graphs
  • You can use unlimited amounts of data
  • It facilitates access to the information you need at the right time.
Maria Gabriela Hernandez profile photo

Cons

  • Resource heavy, jobs, in general, can be very memory intensive and you will want the nodes in your cluster to reflect that.
  • Debugging, it has gotten better with every release but sometimes it can be difficult to debug an error due to ambiguous or misleading exceptions and stack traces.
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  • Tableau is ill-suited to work with SSAS cubes, at least when you are used to analysis within Microsoft tools
  • Data preparation is not up-to-par with other leading vendor tools (although can be improved through Alteryx if you have access to it)
  • The ease-of-use is true for basic analysis, but rapidly gives way to a steep learning curve with more complex queries or when the business context is more mathematics oriented
Charles Saulnier profile photo

Likelihood to Renew

No score
No answers yet
No answers on this topic
Tableau Desktop8.9
Based on 39 answers
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.
Mashhood Syed profile photo

Usability

No score
No answers yet
No answers on this topic
Tableau Desktop8.7
Based on 23 answers
Entry-level data analysis is accessible even to beginners, some advanced analysis is possible, but it is not at this time an end-to-end solution for analytics, though imprvements are coming from version 10.2.
Charles Saulnier profile photo

Reliability and Availability

No score
No answers yet
No answers on this topic
Tableau Desktop8.0
Based on 10 answers
Have seen issues with the vertica DB driver which manifest as errors for the end user.
Paul Morgan profile photo

Performance

No score
No answers yet
No answers on this topic
Tableau Desktop6.5
Based on 9 answers
It performs as well as could be expected; the challenge is making sure the data is organized correctly to optimize performance.
Paul Morgan profile photo

Support

No score
No answers yet
No answers on this topic
Tableau Desktop9.0
Based on 16 answers
Only used tech support by searching the support website for 'how to' and was simple and successful.
Jerry Pritchard profile photo

In-Person Training

No score
No answers yet
No answers on this topic
Tableau Desktop9.4
Based on 4 answers
Extensive and beneficial - users have shown great benefit of training and put it to practical use.
Paul Morgan profile photo

Online Training

No score
No answers yet
No answers on this topic
Tableau Desktop8.0
Based on 4 answers
The training for new users are quite good because it covers topic wise training and the best part was that it also had video tutorials which are very helpful
Chandra Bhanu Pratap Singh profile photo

Implementation

No score
No answers yet
No answers on this topic
Tableau Desktop8.0
Based on 34 answers
Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.
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Alternatives Considered

I prefer Apache Spark compared to Hadoop, since in my experience Spark has more usability and comes equipped with simple APIs for Scala, Python, Java and Spark SQL, as well as provides feedback in REPL format on the commands. At the same time, Apache Spark seems to have the best performance in the processing of large data that works in memory and, therefore, more processes can be downloaded on Spark than on Hadoop, despite the fact that Hadoop is also a very useful tool.
Carla Borges profile photo
Excel is the ultimate jack-of-all-trades Swiss army knife approach. You can do almost anything but it is missing much of the polish of dedicated applications of Tableau. Great for the initial approach to a new dataset. I have created some custom Excel macros that go in and run calculations on combinations of fields -- mostly to see if there are data relationships. This is hard to do almost anywhere else. D3.js is an incredibly flexible tool if you are willing to deal with the tremendous overhead of the associated programming. It has a huge learning curve and I would never recommend it for the exploratory or initial examination phase. But for incredibly detailed and robust displays, it is terrific. Expect to take a week to get anything done right.Lumira is a nice get started and get something out the door product. It still feels like a beta-level product. This could be useful for departments that don't have specialized people or want something more than what Excel offers but aren't willing to pay for the full Tableau license. Good for SAP houses of course but I wouldn't count out the other two.
David Fickes profile photo

Scalability

No score
No answers yet
No answers on this topic
Tableau Desktop7.0
Based on 3 answers
Although tableau is highly interactive and fast but with very large dataset its performance degrades heavily. So up to certain extent its really good but after that we have to take care of its performance issues.
Chandra Bhanu Pratap Singh profile photo

Return on Investment

  • It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
  • Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
  • It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.
Carla Borges profile photo
  • It is very difficult to quantify the effect that using Tableau has had on our clients. The one major benefit I can think of is the reduction of operational expenses. Tableau allows them to keep one person who maintains ten dashboards instead of the twenty people it took when they were using Excel.
  • Having a series of relevant, automatically refreshing dashboards allows for "quick response" to business problems, which could save tremendous amounts of money. If a problem is occurring, you would see it on your dashboard the next day, instead of an analyst finding it a month later.
Brad Llewellyn profile photo

Pricing Details

Apache Spark

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Apache Spark Editions & Modules
Apache Spark
Additional Pricing Details

Tableau Desktop

General
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
Entry-level set up fee?
No
Tableau Desktop Editions & Modules
Tableau Desktop
Edition
Personal
$9991
Professional
$1,9991
1. per user
Additional Pricing Details
Free trials are available for both editions.