Course5 Discovery vs. Shiny

We rely heavily on Course5 for our business decisions every day. It gives us insights that we were really missing before getting set up with Course5.

Incentivized

Shiny is well suited where an organisation is looking to empower their analysts to minimise time spent on repetitive analysis by deploying repeatable analytical pipelines, but also looking for them to add greater value to the organisation by utilising more advanced analytical techniques. Ideally it is well suited where IT are on board and supportive of some of the more advanced features such as deploying R Shiny dashboards.

Incentivized

• Data Visualization.
• Predictive Modeling.
• Trend Analysis.
• Data Analysis.

Incentivized

• Data tables are appealing to look at.
• Enables us to create trend indexes in an effective way.
• Easy to integrate with the rest of my R syntax.

Incentivized

• I do wish there was a feature that keeps a dynamic list of company benchmarks that update in real-time and use that to be a comparison goal line in metrics.
• Some of the SQL syntax highlighting/auto-completion will not work.
• Sometimes text widgets will just "disappear" after I have dragged them onto the canvas.

Incentivized

• Easier ways to connect to data sources
• Better access control for different roles in the organization
• Video material that allows a better learning experience

Incentivized

Having the ability to see data from so many sources for our finance, support, marketing, and sales departments at a glance without having to pull data every day and make pivot tables each time is absolutely critical for us. Our leadership team is able to make crucial business decisions more quickly and more easily thanks to Course5.

Incentivized

- Faster response working with a large amount of data. - R Studio connection and flexibility. - Scenarios modelling.

Incentivized

• We saved time because the analytics were presented in a way that made sense.
• Return on Investment.
• Scalability as a company.

Incentivized

• We saw a good involvement to researchers when showing their models in shiny.
• We can have a quicker review from the user when the model is in production.
• False positives can be found easily and they help the retraining of the model.

Incentivized