SAP Datasphere, the next generation of SAP Data Warehouse Cloud, is a comprehensive data service that enables data professionals to deliver seamless and scalable access to mission-critical business data. It provides a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization. SAP Datasphere enables users to distribute mission-critical business data — with business context and logic preserved — across the data…
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Tableau Desktop
Score 8.4 out of 10
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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.
$1,380
per year (purchased via a Creator license)
Pricing
SAP Datasphere
Tableau Desktop
Editions & Modules
No answers on this topic
Tableau Creator License
$115
per month (billed annually) per user
Offerings
Pricing Offerings
SAP Datasphere
Tableau Desktop
Free Trial
Yes
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
SAP Datasphere is available as a subscription or consumption-based model. The SAP Datasphere capacity unit (CU) offers an adaptable approach to pricing that enables any workload on any hyperscaler. The number of CUs required is determined by the unique workload, with the ability to tailor the combination of required services within SAP Datasphere utilizing a flexible tenant configuration. The services that contribute to CU consumption are the core application (compute and storage), data lake, BW bridge, data integration, and data catalog (crawling and storage).
All pricing plans are billed annually. A Creator license includes Tableau Desktop, Tableau Prep Builder, and Tableau Pulse. Discounts sometimes available for volume.
SAP Datasphere is an exciting way to modernize our data stack, and what clinched it for us was how deep we're already in with SAP - it only made sense to try and leverage the synergies between Datasphere and our other SAP products.
SAP Datasphere is well suited for scalable cloud based data integration scenarios which also opens up the doors for AI driven insights which are much harder to achieve with on-prem data warehouses. Considering the licensing model of SAP Datasphere being based on consumption driven capacity units cost can be a big consideration for organizations with large volumes of data that can be a pre-requisite for data mining and AI use cases. So this can be a bottleneck or not so well adopted scenario for SAP Datasphere.
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).
SAP Data Warehouse Cloud offers free trial for 90 days with free 128 GB of storage and 64 GB memory.
Availability of self-service data modeling and analytics on SAP Data Warehouse Cloud enables users to access and analyze data without getting support from the IT team.
Without zero coding while collecting, connecting, analyzing and modeling data, it saves us time and operational costs of partnering with external IT support experts.
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.
We are moving into using SAP datasphere heavily and replacing all of the SAP HANA native calc view logic to the sap datasphere graphical view which will reduce the legacy SAP BW data warehouse. Also need some more features such as debugging, sql preview and prompts enhancements so that we can generate the reports.
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.
It is one of the best tools and a boon to Logistics teams across the globe. One tends to actually process warehousing data so smoothly and the way demonstration is made while in programs it makes it user friendly. The Inventory touch points that one identify is simply awesome and is best part.
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
I would greatly acknowledge the services of Sap Data [warehouse Cloud] because we were struggling before its arrival where we used to get manual data connections and this used to consume a lot of time but after its use, we now are able to connect data easily saving a lot of time and finances.
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.
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
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.
Each of these listed software has its own unique strength and capacity that scales well. SAP Datasphere on its end up against them with more suitability for large establishments with complex data ecosystems with scalability support. Also, it avails a pay-as-you-go pricing for users, and it is widely up for data quality, data governance, and data discovery.
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.
Despite the pricing model being expensive for small businesses, it provides decent features and capabilities for organizations of different sizes and it's an appropriate investment in today's business environment where there is constant pressure to build a scalable and flexible analytics service
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.
Ever since we implemented SAP Data Warehouse Cloud, we have been able to reduce the additional costs of hiring third-party service providers by incorporating professional services offered by the vendor.
Preserving data quality has enhanced governance on data by having a single source that is accessible to every business user via self-service capabilities.
Operational cost is lowered by connecting data in one integrated solution hence making it easy to access information without having to keeping logging to other applications. Additionally, no external IT support is needed since SAP Data Warehouse Cloud has no-coding modeling tools.
SAP Data Warehouse Cloud has enabled every business user to understand different data by transforming data to real insights.
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.