Oracle CPQ vs. Tableau Desktop

I think CPQ had worked so well for our company because of the widespread nature of our associates and tracking orders that were being placed in multiple time zones. My team specifically needed a way of analyzing these orders to track our progress in real time and sort out any supply orders before they became an issue. If you are in a centralized location with a smaller team then this may not yield much use to you.

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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).

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• Leveraged automation to minimize headcount costs despite 10% year-over-year business growth, and enabled staff to focus on more strategic tasks.
• Established a flexible CPQ system that scales on demand to easily accommodate the company’s multiple global locations.
• Improved customer relations by reducing configuration time and allowing sales more time to meet with customers and close orders.

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• 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.

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• Significant setup time, cost, and maintenance. We have to use an implementation partner
• Does not always play well with other software, even Oracle software. While this is improved and being further improved, that it was a third party acquisition means things sometimes require a little extra care
• Additional setup documentation and first walkthroughs would be helpful, especially if it was all in one place

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• 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

So far it is all good with BigMachines, looking for new features since Oracle acquisition has created a lot of expectations. We have outlined our limitations (out of box functionality) in our periodic customer successor advice meetings for a while, hope we get a resolution soon. Also, the BigMachines user license fee has increased a lot in the last three years.

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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.

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The software UI can be as complex or as simple as you need it to be (depending on the business). It does require training others on quote configuration and the order in which to build out order positions prior to configuring a quote. Once users are trained;however, it is fairly straight-forward. The UI is still more static than other new wizard/drag-and-drop models, but it get's the job done

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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.

Other than one day two years ago and an hour or two a few times since then due to data center outages, it has been very reliable

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.

It depends upon the day however there are so many failure points with online services, including our internet service, that this is probably closer to 9 with the latest version

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

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Some specific support personal was good and fixed some problems fast using proper solutions. But when one of them went to sleep when we had critical issues and they do unreported commits to our production environment which caused issues and they were hiding it?? you can not give more than a two (maybe even that is too much). They also failed to add a feature for us which also bring the grade down.

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.

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They have pretty good training. Our business analysts have been able to go to entry and advanced level training. They have a train the trainer model. Our business analyst attended training, then trained the rest of our staff.

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

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It was a much more technical implementation than we thought. It involved much more code.

Future releases have made and will make administering the tool easier.

EDL consulting had one good developer, but when he was moved off, they were horrible to work with.

The BMI sales team does a “BOA” or a “Business Operation Assessment” which is extremely valuable, not only for them to scope an implementation and get more reach within the organization, but it is also a documentation of business process that most organizations don’t have. It highlights inefficiencies and allows for correction during implementation.

Having a dedicated team (in-house) for implementation is key

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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Oracle engagement is ahead. They are active in the development of the tool and provide great support after implementation. They also listen to their customers and offer opportunities to feedback and provide input through activities like the customer advisory board forum.

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.

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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.

• Increased Sales Rep efficiency. Being able to create multiple quotes ACCURATELY and quickly was a game changer.
• Large implementation time. It's a little difficult to fit BMI into a SCRUM style build, with multiple working models and prototypes of all 3 simultaneously.
• A larger fee for licensing and implementation cost. ROI wouldn't be realized in the first year.

• 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.

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