SAS EG : A wholesome tool to extend analytics capabilities, but cost could be a concern
February 23, 2019

SAS EG : A wholesome tool to extend analytics capabilities, but cost could be a concern

Rohit Narang | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with SAS Enterprise Guide

SAS EG is being used in the Credit Risk Analytics domain within Wholesale Banking for validating models along with build analytics queries for quick refresh & slide-dice data for the regulatory requirements. Also, we often create project files (.egp) to record the flow of codes. Import/export data and the underlying connections among pieces is also stored in one place. It is frequently used for carrying out statistical analysis like ANOVA, univariate, and regressions for model development.
  • EG v7. 1 offers a GUI approach to query building as opposed to predecessors like Base SAS v9.1. It's easy for non-programming background users.
  • EG offers better connectivity with a remote server, while in an earlier version we had to segregate script using "rsubmit' blocks
  • Project files is a great feature (with process flow) in EG which was missing in earlier versions.
  • It's a preferred choice for people with SQL backgrounds, as proc SQL is a quite similar and easy to use procedure.
  • Proc Import & Export usage via code is still a problem, rather one needs to do it manually at times (using the wizard).
  • Visualization capabilities and cost could be an improvement that the next versions should bring.
  • Cost is also a concern compared to other products.
  • Cost vs Technical Support ratio is high.
  • Analytical capabilities have improved department-wise (with credit risk).
Tableau : A good tool for visualisations but SAS is better for running production scripts & using adhoc analysis
Well Suited to:
1. Carry out ad-hoc analysis and use basic statistical reports.
2. Query Builder for users with GUI likelihood to design queries.
3. For writing complex macros once for repetitive tasks & repeating with multiple iterations of different parameters, it is very useful.
Not Suited for:
1. Using pass through to read large datasets could be very resource & time-consuming.

Using SAS Enterprise Guide

1000 - Credit risk model development, portfolio analytics, group reporting teams
58 - Advance Sas certified programmers
System support
Advance Data warehousing
Remote server setup
  • For Credit risk review of Obligors.
  • For New credit product originations & account management.
  • For Collection & recovery strategies.
  • For Predictive Modelling.
  • Integration with Hadoop cluster to enhance connection with multitudes of data sources while maintaining high performance.
  • Setting up Group Stress testing teams onshore who do Monte Carlo simulations and share their set of scenarios to Group Economics teams. It is a data & analytics oriented work and requires SAS along with visualizations with statistics capabilities.
On account of current user experience and the organization-wide acceptance.

Evaluating SAS Enterprise Guide and Competitors

  • Product Features
  • Product Usability
  • Prior Experience with the Product
Organisation wide acceptability and strong positive feedback.
The choice would be SAS Enterprise Guide only until a better product (rather, suite) replaces it in performance & cost both.

SAS Enterprise Guide Implementation

I've not worked hands-on with the implementation team, but there were no escalations barring a few hiccups in the deployment due to change in requirement & adoption to our company's remote servers.

SAS Enterprise Guide Support

Due to a good response from the support & helpline. However, further improvements can be done.
Quick Resolution
Good followup
Knowledgeable team
Kept well informed
No escalation required
Support cares about my success
Quick Initial Response
Yes - As mentioned, it is the choice of features it offers along with the acceptability

Using SAS Enterprise Guide

It is due to the relevance of exhaustive features we use in our department of Credit Risk Analytics & Data modeling, and sharing insights with Group Portfolio Teams
Like to use
Relatively simple
Easy to use
Technical support not required
Well integrated
Feel confident using
  • Adhoc query (using query builder)
  • Simple Interface, Slicing & dicing of data using In-built filters
  • Text mining & predective modelling
  • Web interface of Advance analytics
  • Query builders are very slow with large data (can be learnt from other tools available in market)
  • Need to use Proc Printo to automatically redirect logs to disk, could be automated.