D3.js vs. Shiny

It's well suited for dynamic data, especially when multiple users are using the application and generating data, it helps us to get analytics of the data for users.

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

• It provides multiple ways of visualizing data easily.
• It is fast and light on system resources. It is built with JavaScript and visualizations can be easily hosted on the web across browsers.
• It has a huge community backing it so it is easy to find people to help with whatever you're doing.

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

• Hard to code, not a kids play toy.
• No tutorial from official documentation.
• Requires web development experience.

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

Support can be improved by providing more educational videos.

Incentivized

Protoviz does not require as much knowledge of programming to build visualizations as with D3.js or Google Charts. Highcharts or AnyChart are other alternatives that are more specific to building charts only

Incentivized

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

Incentivized

• Rapid Development using templates helps faster delivery of the project.
• Documentation requires a lot of time to study.
• D3 creates high-quality visual effects which can be used over large screens.

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