Jirav vs. Tableau Desktop

I feel that Jirav would be best suited for companies with less than 75 employees that need a more robust software than Fathom (Quickbooks Onlne integrated FP&A tool based in Australia) that is very customizable, with simple revenue modeling, few personnel changes every month, few departments, no multi currency, and need collaboration only with top-level personnel. I think Jirav is a product that is being highly recommended in the accounting industry for outsourced accounting firms, but accounting only looks at historical information and there needs to more finance industry influence, approval, and input so they can improve their product.

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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• Jirav integrates well with Quickbooks Online (QBO), and I like how you can easily customize the reporting presentation by combining GL accounts and showing more or less details as needed for managerial reporting
• I like that Jirav is browser-based and that I can easily share reports with internal and external parties for comments
• I feel more confident using Jirav than I do with Excel because there is more data validation, and some notifications will appear if there are errors in the model
• The sales capacity model and ramping employees schedule that their implementation / professional services team built for us works well overall (with some limitations)
• Ideally, having a direct integration into Jirav would be great for all our data. However, some of our software didn't have a direct integration, so I was glad that Jirav offered the ability to use a connected Google Sheet that lets me input data that can be imported directly into the system

• 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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• At times, I feel that Jirav is too customizable. It would be great if they could tailor the system to be more industry-specific. For example, if the system could provide standard formulas for SaaS industry metrics already within the system, then that would have saved me a ton of time with having to create the metrics myself. The formula creation for metrics is quite tedious as well because you can only do simple calculations, such as A + B or A x C. You cannot do A + B + C or A x B x C.
• I struggle with the way they have their staff planning set up because I have to reimport an Excel every month with all the changes (new hires, terminations, pay changes), and the changes appear to be retroactive on reports, which doesn't make sense if someone receives a raise or pay change during the year. It would be much easier for planning for bookings if they could add a column for quota by salesperson.
• If there are notifications of errors in the model, then the notifications will continue to present themselves after I resolve the issue. It would be nice if I could clear out notifications I know are not relevant anymore. I also still find errors in the system that I would have expected the system to notify me about, such as Assumptions that are set up but they are not included in any formulas, so I should delete that assumption to prevent anyone from thinking changing that assumption will impact the model.
• There is some functionality for sharing reports and information, but there is not enough granularity in security settings to allow me to share certain information easily. For example, if I want to share information with managers to manage their departments' budget, but also not see their boss' compensation, then it takes some work to set that up. Or, if I want to share a report with a recruiter of planned headcount and salary, then I need to export it to Excel first and delete Actual headcount and salary, so they don't see current employees' compensation (including the person's boss' salary).
• Customer and vendor names do not import, only the totals, so if you look at Actuals vs Plan, the actuals will show a total figure and the plan will show detail, creating the need for an external and manual reconciliation
• There is no multi-currency available
• Scenario analysis can be difficult to do quickly. For example, if I want to see the plan with planned hires and without planned hires, then I would need to create two separate plans, individually select and delete the planned hires in one plan and keep then in another plan, which is time-consuming
• Using Google Sign-In causes the system to time-out frequently for me, so I get kicked out of the system and have to log back in. If I have multiple tabs of Jirav open, then re-logging in sometimes doesn't bring me back to where I was originally at.
• You can export reports to Excel, but there are no formulas of the calculations, which makes it more difficult to understand how calculations are being performed unless you look in the browser and dig into the calculations. This also might make it more difficult if you decide to go to another software in the future since you may need to start from scratch in the next software
• Seasonality has been difficult to model. For example, the way our model is set up, I can use an assumption for Q1, Q2, Q3 and Q4. However, if I update Q3 for this year, then it also updates Q3 of all subsequent years, which I don't want. A more complex model and additional maintenance would be needed to accomplish more accurate seasonality planning

• 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

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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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

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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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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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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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Fathom was the cheapest and most basic as an add-on directly to QuickBooks Online Plus, but you lose functionality with Fathom if you use QuickBooks Online Advanced (QBOA). The main loss of functionality for me was the lack of multiple department reporting, which was absolutely necessary for my analysis. Jirav was half the price of Moscaic.tech, but I've heard Mosaic has standard metrics for the SaaS-industry, which is appealing after going through the tedious process of setting up metrics in Jirav. QBOA has additional reporting than QBO Plus, but not enough robust features for planning and modeling. PlaceCPM is Salesforce-based and a I felt having a strong Salesforce admin that can great reports made their unnecessary, and I feel like most of the time you need a Salesforce admin just to run Salesforce. Cube, Vena and OnPlan are spreadsheet-based, but I don't want to use spreadsheets. Prophix, Board and Anaplan seem outdated. Workday was more than what I needed

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.

• 1-3 day shortening of post-month end close analysis from integration with our accounting software
• Elimination of several manual Excels related to headcount variance, salary variance, and planning

• 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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