Mode Analytics vs. Tableau Desktop

After launching a new contact pathway in a help experience, Mode Analytics can help provide insight into the sentiments from users as well as the engagement with any written content. Numeric outputs are easier to manage, whereas more nuanced/emotional feedback is sometimes hard to quantify (though not impossible if you get creative).

Incentivized

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

• Easy to use (click a button and get right to SQL).
• Security First (everything is locked down by default).
• The White Label feature is super easy to skin -- our embedded reports look just like our app!

Incentivized

• 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.

Incentivized

• Date ranges aren't always the most intuitive to set, strangely
• Faster refresh rates would be ideal
• Would love more dynamic mobile device integration (alerts, etc)

Incentivized

• Formatting the data to work correctly in graphical presentations can be time consuming
• Daily data extracts can run slowly depending on how much data is required and the source of the data
• The desktop version is required for advanced functionality, editing on [the] Tableau server allows only limited features

Incentivized

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.

For the advanced user already familiar with Python. It is just the same tool, already managed and connected to the data.

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

Mode has dedicated agents who are online in a chatroom, ready to take on any questions and provide helpful feedback.

Incentivized

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.

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

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.

Incentivized

• Tableau is a huge pain to edit or create dashboards, by comparison. It can make better looking visualizations, but in practice, letting users drill down and change dimensions slows the end user experience so much that it's often not worth it.
• Looker is amazing for data modeling, but you have to get your whole business all in on it to take advantage. Viz capabilities are similar.
• Databricks has a lot of functionality overlap, but the visualizations are terrible. Databricks' great strength is that you can use notebooks to do anything with code.

Incentivized

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.

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.

• It has allowed us to monitor ongoing financial transactions written to our SQL data tables in real-time and that helps us to monitor user transaction activities in real-time
• Using Mode we have been able to also track users who undertake fraudulent financial transactions; preventing financial losses to our users
• Mode's collaborative abilities have been very helpful in sharing transaction monitoring workload across our compliance and cybersecurity team

Incentivized

• Easy to share and manage viewer access on a different level to help identify fraud.
• Faster report generation, increased revenue, better decision-making, and data storytelling.
• One-click access to business health and the ability to build/maintain more effective and efficient reports.
• It's easy to share and even manage access to viewers on a different level, and reports are done in a more visual and storytelling manner.

Incentivized