Item: Posit
Rating: 9
Author: Akshat Garg

Use Cases and Deployment Scope

We use RStudio to build data science and machine learning pipelines for AI models. The pipeline that we create on R studio help in end-to-end data processing, cleaning, RDA, model training, and prediction. The scripts that we write on RStudio are also used for automation and creating machine learning tools using R shiny as well.

Pros and Cons

Data processing
Data visualization
Machine learning
Tool development (Rshiny)

User interface

Return on Investment

Faster data processing
consistent pipeline creation

Alternatives Considered

Jupyter Notebook

RStudio works really well compared to competitors such as Jupyter Notebook where there is no environment to visualize variables. RStudio on the other hand is much easier to use and provides the right set of environments for users.

Key Insights

Do you think Posit delivers good value for the price?

Yes

Are you happy with Posit's feature set?

Yes

Did Posit live up to sales and marketing promises?

Yes

Did implementation of Posit go as expected?

Yes

Would you buy Posit again?

Yes

Other Software Used

Jupyter Notebook

Likelihood to Recommend

RStudio is well suited for data processing and visualization. The tool provided a very interactive and user-friendly environment to understand each step in the data processing. However, RStudio lacks in adoption among the data science community as python is not available and most of the machine learning libraries are custom built for python.

Rstudio - The most convenient ML tool

Overall Satisfaction with RStudio