Tableau Desktop vs. Workday Prism Analytics

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).

Incentivized

In my organization, we mainly use Workday Prism Analytics in HR and Finance departments. It not only enables us to make data-centric decisions but also helps reduce the need for data experts since we are able to visualize data on our own through self-service analytics.

Incentivized

• An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
• Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.

Incentivized

• It's web based. No need to install any desktop clients on your machine to use platfora.
• It's best suited for a big data Hadoop environment. I can rate it as the #1 BI tool for a big data hadoop environment.
• Platfora follows kind of the same architecture as Hadoop architecture like Master and Slave architecture. It scales with the data volumes.
• Querying data is very good and very fast. (Platfora Lens)
• Client presentation wise it's good. You can get different kinds of graphs.
• Platfora almost supports everything on Big Data technologies including file formats, compression etc.
• Security is not compromised and it can deal in parallel with any Hadoop distributor security implementations. Just take an example of Knox on Hortonworks, so it will deal with that and cloudera , MapR
• Its very easily understandable and for the new people who wants to try platfora, learning curve is low
• You can create your own datasets in platfora. You can store your results as a dataset in platfora and can share across

Incentivized

• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

• Data Movement - Data needs to be moved from Hadoop to Platfora to create Platfora Lens and to do analytics.
• To support Data movement, infrastructure cost is high.
• To support data movement, network bandwidth consumption is high.
• No trial versions for companies to evaluate.

Incentivized

Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.

Incentivized

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

Incentivized

Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.

Incentivized

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

Incentivized

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.

Incentivized

I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.

Incentivized

Both are great products. The advantage of SAP Workforce Analytics is that it's widely interoperable between different APIs and databases. Having said that, Workday Prism Analytics scores much better in user-friendliness and the learning curve for the teams to start using it is very low. If Workday enhances its APIs functionality, it can compete easily with SAP Workforce Analytics.

Incentivized

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.

• Tableau was acquired years ago, and has provided good value with the content created.
• Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
• Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.

Incentivized

• Improved ROI by decreasing the necessary time investment that managers must make to upkeep employee data sectors.
• Improved ease of access for employees, reducing unnecessary communication between employees and management.
• Has led to fewer accounting errors overall.

Incentivized