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
Workday Prism Analytics
Score 7.1 out of 10
N/A
Workday Prism Analytics is a scalable data hub that enables Finance and HR to securely ingest, blend, and transform high volumes of data from any source—integrated with Workday’s people and financial data. Prism Analytics powers deeper insights across Workday HCM, Financials, and Adaptive Planning, helping teams make smarter decisions without heavy IT reliance. Built on a high-performance Spark engine with machine learning-based resource management, multi-cloud support, and a tables-based…
Both power bi and Tableau Desktop has its own pros and cons. Microsoft power bi is best to work with Microsoft products. however for fast connection with diverse range of integration with data sources Tableau Desktop is best. if you are cost sensitive power bi is best option …
Tableau is more flexible than these - I liked Qlikview old version a lot but have not used the Qlik Sense etc new ones. Tableau user logic is harder to understand than Looker Studio. However it's more trust worthy. Connecting internet sources to Tableau Desktop is much harder. …
Tableau Desktop is older and just better overall. It has more capabilities and is more useful to have. I don't think you could have Alteryx as a standalone product like you can with Tableau Desktop. You'd want another bi tool.
Tableau Desktop has a more easy to use drag and drop interface and is easier to learn. It also allows greater customization of charts than Power BI. However, Tableau Desktop costs more than Power BI which is bundled into our Microsoft contract at no additional charge. Power BI …
The visualizations are far and away more powerful and it is more user friendly than Power BI. It would take 3-4 times as long to create the types of reports in Excel that I can create in Tableau Desktop and there are a slew of ways I can present the data in Tableau Desktop that …
It has a better user interface compared to Microsoft Power BI. The Tableau integration process is quite simple and clear with the third-party application whereas Power BI is not easily integrated with other tools and requires a complex process to follow for integration. DAX …
When it comes to pricing, Tableau is kinda expensive but worth it as it has more features, not just features but really useful features that make our work easier especially as a project manager I need to pull up data almost every day in our meetings, and I find Tableau useful …
Tableau can create visually attractive customizable dashboards than can quickly by drag-drop while in power bi we can create simple dashboard. Power bi support lesser data source while in Tableau there is a lot of options When we talk about data handling tableau is a clear …
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 …
Tableau Desktop provides some state of the art feature and capabilities that are just awesome. Its support, online blog, and tutorials are better than its competitors. That was the best selling point for me.
With Tableau Desktop, it's easy to create a report in the
context quickly. It allows for the seamless management of the data sources,
which is convenient for the data users. Because it is simple to use, it is
It does have a lot of potential when using Microsoft other technologies - in integration/Embedded, Visuals and connectivity to data sources. Advanced analytics is also smooth when working on python/r scripts. Automated insights are better in Tableau/Alphaa AI. NLG/NLQ - …
For complex data visualization, Tableau Desktop shines. Even though it uses highly granular databases, it has a powerful engine that can process large amounts of data quickly and produce high-quality charts. It has the broadest range of APIs and is extremely simple. The …
We decided to use Tableau Desktop as that's fairly standard in the industry, it is being taught in college, and is widely known. Tableau Desktop is nice, but in my opinion, it is VERY expensive. Unless you are really making money off of decisions, then your ROI is going to be …
Using Tableau Desktop, we have found it the most actionable and user-friendly application ever. It has the broadest range of APIs and is exceptionally user-friendly. It can handle a large amount of data and produce smooth charts quickly. For data geeks, this is the ideal stack.
When compared to Power BI, Tableau has a more flexible deployment. You can install the desktop version without having to install the SQL server. Tableau got you covered end-to-end — from collaboration, analytics, content discovery, data prep & access, down to deployment. …
Tableau Desktop is preferred over other BI software because it allows for more data visualization, storytelling, and dashboards. Microsoft Power BI may be a better option if you need to perform data modeling, however. Tableau Desktop is an excellent tool for nearly all other …
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 …
Tableau Desktop is the most user-friendly and actionable application we have used in comparison to others. It has the best API connection potential along with easy start-up. They seem to always be updating the platform to solve newer problems which help keep my company up to …
We also use Power BI for small projects and teams that can't afford to pay for Tableau licenses. Tableau has more features and is more robust compared to Power BI. They also provide better and faster support compared to Microsoft. It is the standard visualization tool, but …
For databases or types of data that have high granularity and details, Tableau Desktop is better to plot and help visualize every detailed behavior with a great performance. It's engine can process a massive amount of data and generate a smooth chart without spending too much …
Visier People wasn’t rapid to gather data across ETL services mainly from on-premise data sources. Hence, we shifted to Workday Prism Analytics which is absolutely fast in data collection, preparation, modeling, and visualization.
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 …
The thing about Workday is it has everything. It is not one single dedicated program to one single thing. So, naturally, each service/ability it has could and I'm sure will improve in time to be a bit more specific. This is still pretty impressive for a program that integrates …
Price wise Workday Prism Analytics provides Better value for money compared to them considering the wide range of features it offers for both HR and Finance problems. strong integration with Workday parent tool makes it a wholesome package unlike the other two. Data integration …
Workday is easier to be integrated than successfactors. Employee can initiate and guide the requestor for any required information to submit and put forth the request. All parties are notified real time through Workday. Another ease of usuage is Workday can be accessed from …
We use both within the company. I like Workday more because Workday doesn't crash often. You also don't have to be changing any times that you change your workflow. Workday also has the learning modules while inContact is just for tracking work. They're both used but it seems …
[Workday Prism Analytics]'s product support is more preferable when comparing the two. [Workday Prism Analytics]'s data modeling had a more interactive and user-friendly interface. Inexperienced new hires can quickly catch on to the software, even if they’re unfamiliar with the …
I have no experience [with] similar analytics platforms though this is the best tool I have worked with. [It has a ] great impact on our organization. The intuitive tools with this platform get most of our company programs [to] run smoothly. It offers challenges that face our …
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).
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.
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.
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
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.
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.
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.