Statistical Modeling at its best
June 12, 2019

Statistical Modeling at its best

Maria Carver | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with RStudio

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.
  • Very Intuitive and user-friendly.
  • Can perform statistical modeling for extrapolating and also automating repetitive tasks.
  • Good for people with less coding experience.
  • 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.
  • The return on investment is very high and quick. It has great potential, especially in the oil industry, which depends upon assumptions.
  • It should be integrated with more processes, to increase the value gotten out of it.
  • It should also be integrated with more applications.
Python is a major competitor, but Python is lacking when it comes to statistical modeling. Also, people with less programming experience can use RStudio better than Python.
Red Hat Virtualization (RHV) (formerly RHEV), Microsoft Power BI, Petrel E&P
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.