Posit Reviews & Insights

Score10 out of 10

235 Reviews and Ratings

Community insights

TrustRadius Insights for Posit are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Intuitive User Interface: Users have found RStudio to have an intuitive user interface that allows them to quickly test and debug code. This has been mentioned by numerous reviewers, highlighting the ease of use and convenience it offers in coding tasks.

Seamless Integration with Git: The seamless integration of RStudio with Git has been praised by users, making it easy for them to manage version control. Several reviewers have specifically mentioned this as a major advantage of using RStudio for their coding projects.

Powerful Statistical Analysis Tool: Many users appreciate RStudio's capabilities as a powerful tool for statistical analysis and data exploration. They mention its ability to import data from multiple sources, apply machine learning models easily, and export data into various channels.

Posit Reviews

15 Reviews

Engineering

Everyday Statistical Workbench

Rating: 10 out of 10

Incentivized

April 13, 2022

Use Cases and Deployment Scope

We use RStudio for analytics, data science, reporting, and statistical modeling for business clients in all enterprise functional groups. The system is extensible to a wide array of use cases, including quality, machine reliability, finance, supply chain, marketing, and business intelligence. RStudio connects to our Azure and on-premise data assets.

Pros

Data visualization
Big data
Statistical modeling
R
Python
Web sites

Cons

Databricks
Azure DevOps

Likelihood to Recommend

RStudio is the premier statistical workbench and development environment for professionals. It is well suited for serious data science and statistical analysis on local compute hardware and in the cloud. RStudio is not a graphical toy.

Jim Gruman

Senior Program Manager in Engineering at CNH Industrial (Automotive, 10,001+ employees)

Vetted Review

4 years of experience

View profile

Makes life easier for analytics developers

Rating: 10 out of 10

Incentivized

July 6, 2021

Use Cases and Deployment Scope

We employ dozens of R users and install RStudio on our machines so that everyone has a familiar integrated development environment (IDE). We also purchase the commercial product RStudio Connect for our analytics teams to develop and share interactive tools with non-technical users. It allows our more experienced R users to create more advanced tools than on our other intelligence platforms.

Pros

Being a complete IDE
Integration with RStudio Connect
Easy to install and administrate

Cons

Could have better integration with free hosting solutions

Likelihood to Recommend

RStudio is perfect for any team that wants to use R. Any team that needs to do advanced data analytics should consider using R and RStudio because both are free, powerful, and industry-standard in some fields.

Verified User

Team Lead in Engineering (Government Administration company, 10,001+ employees)

Vetted Review

5 years of experience

RStudio just works out of the box

Rating: 10 out of 10

Incentivized

March 11, 2021

Use Cases and Deployment Scope

Our organization has devoted considerable resources to implement RStudio across the firm. We have dedicated servers, a team of specialists on staff to manage them, and many individuals who use the product. We use RStudio to analyze data in many forms--AMI data, utility participation data, survey response management, etc.

Pros

Code completion is a life saver when I vaguely know the function or variable and the popup fills in the correct choice
Help on function definitions right in the tool; no need to search the web
Repositioning panels on the fly allows me to minimize parts that matter and get more room for my analysis in the console or in the R file
Built in Git helps me remember to keep the repo current

Cons

Code formatting sometimes rearranges code that was formatted the way I wanted
There is a bit of a learning curve setting up projects, and it makes folders even if I already had them; perhaps modal on what each choice would do might help
We do not save environment when closing, perhaps include a one time for all checkbox

Likelihood to Recommend

RStudio is well suited to be a full IDE for R projects. We do regular R, R markdown, Shiny, and even some Sparklyr. If you need to see inside your data with R, the tool is a good choice. I appreciate that RStudio is open source so I can run a copy on my local machine for quick checks. We also have RStudio for multiple users and access the IDE on servers through Chrome. This allows us to run larger projects and keep them running for longer. The downside of multiple users on a server is that invariably something freezes. Running on the remote server often requires the team to restart and notify everyone.

Andrew Erickson

Senior Consultant in Engineering at Guidehouse (Utilities, 1001-5000 employees)

Vetted Review

5 years of experience

A scalable and robust data science lab and collaboration platform

Rating: 9 out of 10

Incentivized

February 22, 2021

Use Cases and Deployment Scope

We are using RStudio Teams as central lab and prototyping environment for our Data Scientists. We use RStudio Connect to share plots, prototype dashboards and APIs with our colleagues, stakeholders and software developers.

RStudio is part of our internal data science platform and it is being used across product lines within our division (Industrial Applications).

RStudio Teams addressed the problem of having a prototyping environment for everyone. Users can decide which IDE would like (JupyterLab, RStudio, VScode) instead of forcing them to go with the default classical cloud Jupyter environment.

Pros

Close to open source.
Kubernetes integration.
Run on-premises.
Cloud agnostic.

Cons

A bit hard to set up.

Likelihood to Recommend

Centralized Prototyping Environment.
Self-service shiny deployment with minimal ops required.
Self-service API deployment with minimal ops required.
Matching Python and R users in the same place.
Separation between interactive sessions and on demand jobs.

Edgar Bahilo Rodríguez

Lead Data Scientist (Industrial Applications) in Engineering at Siemens Energy (Oil & Energy, 10,001+ employees)

Vetted Review

1 year of experience

View profile

RStudio for life sciences data science

Rating: 8 out of 10

Incentivized

December 22, 2020

Use Cases and Deployment Scope

We use RStudio for our Data Science work in cancer research. It is used by our Informatics department. We have multiple external systems that house our research data, and RStudio addresses the business problem of providing an environment for doing interactive analysis on that data using a controlled package environment, as well as a place for publishing dashboards for non-technical users to explore our data.

Pros

Interactive programming environment in R
Controlled package environment with docker containers
Management of users with authentication
Management of user sessions with clear options and flexibility

Cons

Management of docker containers for programming environments (ease of use)
Process of deploying dashboards to RStudio Connect (specifically package versioning and management using packrat and RStudio Package Manager is difficult)
Occasional lags and bugs in spinning up sessions or working interactively

Likelihood to Recommend

RStudio works well for providing data scientists with an interactive programming environment, or for developing R packages.

The tools are not really developed to be seamless for controlling the R environment or doing "production" or highly reproducible analysis.

Verified User

Director in Engineering (Research company, 51-200 employees)

Vetted Review

6 years of experience

A must-have expansion to R core!

Rating: 6 out of 10

Incentivized

December 20, 2020

Use Cases and Deployment Scope

We use RStudio as a way to quickly develop and deploy proofs of concept that we can deploy to a core group of users before embarking in a broader industrialization process. It allows us to own the entire process and rapidly bring in code fixes or improvements as requested by the power users.

Pros

Deploying known processes already built in R.
Easily producing UI's for triggering known processes in R or SQL.
Creating dashboards.

Cons

Creating landing pages / managing the environment as a whole.
Monitoring app usage.

Likelihood to Recommend

Currently RStudio is the only environment that we have that allows to deploy apps to our internal users, so in many cases it's the best tool to achieve this purpose (instead of building / compiling executables for instance). We have a small team that is good at RShiny so that's sometimes the challenge.

Verified User

Manager in Engineering (Insurance company, 1001-5000 employees)

Vetted Review

3 years of experience

Well Suited for Data Visualization and Modeling

Rating: 10 out of 10

Incentivized

December 8, 2020

Use Cases and Deployment Scope

We use RStudio as an GUI interface for R, which we use to visualize and model data. For modeling data, we use lots of machine learning techniques like Regression, and R provides an excellent package to implement various flavors of regression like lasso and ridge regression. For data visualization we also use Shiny apps.

Pros

Debugging
Front-end interface to R
Provide shortcuts to some R commands

Cons

RStudio connect experience was not very smooth
Web service configuration for the RStudio server is not very intuitive
Some Visual DataGrid GUI would be beneficial

Likelihood to Recommend

RStudio is well suited for individual data visualization and modeling work. R has some very good modeling packages like glmnet. R also has some very good data manipulation package like tidyverse. Data visualization capabilities are also great. RStudio provides a great user interface to R for harnessing the capabilities that I mentioned above.

Verified User

Engineer in Engineering (Health, Wellness and Fitness company, 1001-5000 employees)

Vetted Review

2 years of experience

The R-Studio suite is a well thought out solution to development, control and publishing r apps and services.

Rating: 8 out of 10

Incentivized

December 3, 2020

Use Cases and Deployment Scope

RStudio is a great way to allow teams to develop r-shiny apps without needing to go and install lots of software on each developer's individual machine. It helps people to get ideas together much faster that you can traditionally. And by pairing it with other products in the suite you can then deploy them to non-devs too for quick feedback.

Pros

Centralised admin
Ability to manage allocations of CPU / RAM per user
SSO

Cons

Set up can be complex
Automated updates via the admin screens

Likelihood to Recommend

It's good for teams who are semi-technical but may not be traditional developers, having all the best practices that that entails.

It's more a tool to get a idea out and in front of people as quickly, so that you can see which apps have traction with end users so they can be further developed.

Verified User

Engineer in Engineering (Insurance company, 10,001+ employees)

Vetted Review

1 year of experience

RStudio--Standing on the shoulders of giants

Rating: 10 out of 10

Incentivized

November 17, 2020

Use Cases and Deployment Scope

We model economic indicators for cities in Mexico. Traffic congestion and other demographics.

Pros

Coordinate data wrangling with visualizations
Interactions with other software
Project management
Function name autofill

Cons

Speed
More and clearer detail on dashboard bugs

Likelihood to Recommend

Communicate data insights in a clear and swift way. Code is easy to debug. It is very intuitive and hence, easy to learn.

Emilio Cabrera

Business analyst in Engineering at Independent (Capital Markets, 1-10 employees)

Vetted Review

4 years of experience

View profile

Statistical Modeling at its best

Rating: 8 out of 10

Incentivized

June 12, 2019

Use Cases and Deployment Scope

RStudio is a powerful application when it comes to analyzing data using statistical modeling. It is used by different departments within the organization, especially the data science group. In the production department, statistical modeling is helpful in extrapolating the production volume and rate. RStudio is intuitive and user-friendly. The documentation is very informative and gives deep dives into the functionality. It's also very well integrated with other applications.

Pros

Very Intuitive and user-friendly.
Can perform statistical modeling for extrapolating and also automating repetitive tasks.
Good for people with less coding experience.

Cons

Not as integrated as Python is with other applications.
Objects are generally stored in physical memory, which hogs the memory.
RStudio is slower than many other statistical modeling packages.

Likelihood to Recommend

For extrapolating the production rate and volume, it is very well suited. Different statistical models are applied to identify the right volume in the reservoir. It's not suited for very large data sets since the physical memory is used to store the objects, which kind of limits the usage of RStudio.

Maria Carver

Production Specialist in Engineering at The Dow Chemical Company (Chemicals, 10,001+ employees)

Vetted Review

3 years of experience

View profile

Loading Reviews List....

Video reviews

View playlist