Digital Adoption

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Web and Video Conferencing

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Mobile App Development

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Development

Online Learning

Education

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Collaboration

Enterprise

Accounting

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Management

Payroll

Recruitment Automation

Resume Parsing

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AI Agent Builder

App Development

Browser

Cloud Storage

Component Content Management

Data Center Infrastructure Management

Fraud Detection

Hosted Virtual Desktop

Hyper-Converged Infrastructure

Integration Platform as a Service (iPaaS)

Internet of Things (IoT)

Managed Print

Network Performance Monitoring

Process Mining

Security Awareness Training

Software Defined Storage (SDS)

Solid State Drives

Tower Servers

Virtual Desktop Infrastructure (VDI)

Virtual Private Network (VPN)

VoIP Monitoring

Web Application Firewalls

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Business Card Scanning

Content Management

Data Management

Digital Analytics

Digital Experience Platforms (DXP)

Email Management

Email Marketing

Event Registration

Graphics

Heatmap and Session Recording

Marketing Automation

Marketing OS

Online Reputation Management

Real-Time Interaction Management

Search Marketing Intelligence

Social Media Management

Social Media Publishing

Survey & Forms Building

Swag Management

Web Analytics

Marketing

Business Caller ID

Project Management

Professional Services

Customer Relationship Management (CRM)

eCommerce

Sales

Assisted Living

Car Rental

Church Management

Construction Accounting

Jail Management

Vertical-Specific

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### Data Analysis Techniques
Users generally believe that SAS Enterprise Guide excels in data analysis techniques, providing powerful tools for analyzing and modeling data efficiently. The software's ability to handle large volumes of data and its user-friendly interface make it a preferred choice for conducting in-depth data analysis and forecasting activities. While some users find the cost of licensing to be a drawback, the overall consensus is that SAS Enterprise Guide's data analysis techniques capabilities are robust and beneficial for various analytical tasks.

### Predictive Modeling and Machine Learning
User feedback on SAS Enterprise Guide's predictive modeling and machine learning capabilities is mixed. Some users praise its ability to efficiently create complex statistical models and perform predictive analytics, especially in the finance and energy sectors. However, others express concerns about the platform's limitations in advanced machine learning modeling and graphical representation. Despite its strengths in handling large datasets and offering a user-friendly interface, there are reservations about its adaptability to cutting-edge machine learning techniques available in other tools like Python.

### Advanced Analytics Capabilities
Users generally appreciate the advanced analytics capabilities offered by SAS Enterprise Guide, citing its ability to handle scenario analysis, stress testing, and advanced modeling tasks effectively. While some users find the tool lacking in advanced statistics capabilities for AI/ML, the majority acknowledge its strength in facilitating complex analytics processes. The integration with other SAS products and technologies further enhances the tool's analytical prowess, enabling users to leverage a wide range of advanced analytics functionalities within a cohesive environment.

### Data Manipulation and Cleaning
User consensus seems to be that data manipulation and analysis capabilities are a strong point of SAS Enterprise Guide. Reviewers appreciate the ease of querying datasets and transforming data to meet specific requirements. Users find the tool efficient for handling large datasets and performing functions like emailing results. The software's ability to handle big data and simplify data manipulation tasks is highlighted as a key benefit. However, some users note concerns about processing times and the need for improved project module run sequence organization. Despite these minor drawbacks, SAS Enterprise Guide is generally praised for its data manipulation and cleaning functionalities.

### Large Dataset Handling
Users generally praise SAS Enterprise Guide's capability to handle large datasets efficiently. The software's performance in managing substantial amounts of data is acknowledged as a strong suit by many reviewers. However, some users have expressed concerns about the tool's speed when dealing with complex queries or working with particularly large datasets. Despite this, the general sentiment leans towards SAS Enterprise Guide being a reliable option for handling extensive data sets effectively.

### Statistical Analysis Tools
Users generally appreciate the statistical analysis tools offered by SAS Enterprise Guide, citing its ability to handle complex statistical analyses with ease. While some users find the software's statistical analysis capabilities to be a strong point, others mention limitations in terms of customization and speed when dealing with large datasets. The consensus leans towards acknowledging SAS Enterprise Guide as a reliable tool for conducting statistical analyses, especially for users across different levels of expertise.

### Programming and Code Integration
User consensus seems to be that SAS Enterprise Guide's programming and code integration capabilities receive mixed reviews. While some users appreciate the ease of use and the low-code, no-code options for data analysis, others express concerns about the high cost and the challenges in integrating with other open-source software. The tool's ability to handle large datasets efficiently and its compatibility with various data sources are highlighted as strengths, but there are also mentions of performance issues, slow code execution, and difficulties in SQL coding and data export. Additionally, the lack of support for certain machine learning techniques and the high licensing costs are areas of improvement suggested by users.

### Workflow and Process Automation
Users across various industries consistently highlight the efficiency and convenience of SAS Enterprise Guide's workflow and process automation capabilities. The drag-and-drop functionality, coupled with the ability to automate repetitive tasks, streamlines data processing and analysis workflows. While some users have suggested minor improvements for enhanced flexibility in organizing and moving programs within process flows, the overall sentiment leans towards the platform's effectiveness in managing complex data processes efficiently.

### User Interface and Usability
Users generally praise SAS Enterprise Guide for its user-friendly interface and efficient drag-and-drop functionality. The consensus among reviewers is that the software's interface is intuitive and facilitates smooth navigation through various tasks. While some users appreciate the simplicity and ease of use offered by the drag-and-drop feature, others highlight the need for more customization options in the dashboard. Additionally, there are mixed opinions regarding the software's performance with large datasets, with some users experiencing delays in processing time. Despite these minor drawbacks, SAS Enterprise Guide's user interface and usability capabilities are generally well-received by a diverse range of users.

### Reporting and Visualization
Users generally appreciate SAS Enterprise Guide's robust data visualization features, which allow for intuitive creation of graphs and charts. However, there are concerns about the software's reporting capabilities, with some users finding the graphical representation lacking in customization options and visual appeal. While the tool excels in data visualization, improvements in the reporting aspect could enhance the overall user experience and efficiency in sharing insights with stakeholders.

### Performance and Speed Optimization
Users generally praise SAS Enterprise Guide for its robust performance and speed optimization features, though some express concerns about its integration with big data and performance monitoring capabilities. While many users appreciate the software's ability to handle large datasets efficiently and generate accurate predictive models, there is a notable desire for improved tools to enhance performance monitoring and streamline integration with external platforms like Spark and Python. Despite these challenges, the consensus leans towards acknowledging SAS Enterprise Guide's strengths in optimizing speed and performance for data analysis tasks.

Reviewers highly recommend SAS EG as an effective ETL tool for handling large datasets. They appreciate its efficient data extraction, transformation, and loading capabilities, making it suitable for data analysis tasks. Additionally, users commonly praise SAS EG for its ability to meet regulator compliance requirements, thanks to its robust features and functionalities in this area. With these recommendations, it's evident that SAS EG is a reliable choice for working with large datasets and ensuring regulatory compliance.

Difficult User Interface: Several users have expressed frustration with the user interface of SAS Enterprise Guide, finding it difficult to navigate and slow to develop. They have mentioned that there is excessive clicking required, which slows down their workflow.

Lack of Data Viewing Capability: Some users have highlighted the software's lack of ability to view data on the fly as a major drawback. This limitation makes it challenging for them to assess the impact of changes they make, hindering their decision-making process.

High Licensing Costs: Many reviewers believe that SAS Enterprise Guide is not worth its high price tag. They feel that the software does not provide enough value compared to free alternatives like Pandas, R Studio, and Python.

SAS Enterprise Guide is a versatile software that is widely used across various departments within organizations. Users appreciate its ease of use and quick learning curve, making it accessible to both beginners and experienced analysts. With this software, users can conduct data statistics and data quality verification, query databases, forecast future trends, and visualize data in a meaningful way. It empowers users to perform advanced analytics tasks, particularly those who are more familiar with spreadsheet-type work.

The application of SAS Enterprise Guide extends beyond basic analytics and is commonly utilized in different domains such as Credit Risk Analytics within Wholesale Banking. Here, it helps with model validation and analytics queries. Furthermore, users rely on the software for statistical analysis such as ANOVA, univariate, and regressions for model development. Across multiple business units like marketing, HR, and risk, SAS Enterprise Guide aids in data preparation, ad-hoc queries, and data exploration.

One notable feature highly valued by users is the ability to schedule, run, and keep a version history of processes from a SharePoint site. This functionality ensures the reproducibility of analyses and offers a convenient way to track progress over time. Additionally, SAS Enterprise Guide excels at data cleaning, manipulation, and analysis activities. It handles large datasets effortlessly while allowing users to export cleaned data for further examination or visualization.

Overall, SAS Enterprise Guide is praised for its versatility in solving complex analytical problems across departments such as finance, marketing, operations, and risk management. Whether it's generating reports, performing deep analysis on large datasets or shaping data for specific needs - SAS Enterprise Guide proves to be an indispensable tool for businesses aiming to leverage their data effectively.

Flexible in working with different data sources: Users have praised SAS Enterprise Guide for its flexibility in working with various data sources, making it highly adaptable for different teams. Some reviewers specifically mentioned that this feature allows them to easily integrate and analyze data from multiple databases or file formats.

Easy generation of SQL code: Reviewers who may not be proficient in SQL appreciate the ability of SAS Enterprise Guide to generate SQL code easily. This feature simplifies the process of querying databases and extracting relevant information, enabling users to perform data analysis tasks without extensive programming knowledge.

Point-and-click interface for easy data manipulation: The point-and-click interface of SAS Enterprise Guide is highly appreciated by users as it allows them to create graphics, transform data, and perform statistics without the need for extensive programming knowledge. Several reviewers mentioned that this feature enables them to quickly access and manipulate data, saving time and effort in their analyses.

Designer Desktop

Designer Cloud Professional Edition

RapidMiner is a data science and data mining platform, from Altair since the late 2022 acquisition. RapidMiner offers full automation for non-coding domain experts, an integrated JupyterLab environment for seasoned data scientists, and a visual drag-and-drop designer.  RapidMiner’s project-based framework helps to ensure that others can build off their work using visual workflows or automated data science.

Professional

AI Hub

RapidMiner

SAS Enterprise Guide

Predictive Analytics

Likelihood to Recommend

Likelihood to Renew

Usability

Support Rating

Implementation Rating

SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. With innovative business applications supported by an enterprise intelligence platform, SAS helps 45,000 organizations improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW®.

IBM SPSS Statistics

Spotfire Data Science, feature

IBM SPSS Modeler

IBM Watson Studio on Cloud Pak for Data

Senior Data Scientist

SAS Enterprise Guide 2020-12-01 10:37:23

Tableau Desktop

Posit

Consultant

SAS Enterprise Guide 2019-03-28 11:00:45

QlikView

Assistant Vice President

SAS Enterprise Guide 2019-01-30 22:39:10

Consultant BI senior - spécialité SAS

SAS Enterprise Guide 2018-07-25 09:21:14

Qlik Sense

Microsoft Teams

SAS Enterprise Guide 2020-04-21 09:44:52

TrustRadius is a technology and business research firm based in Austin, Texas. The company is known as a review platform for verified B2B technology and software reviews through a proprietary algorithm and human verification.

TrustRadius

Time consuming

External databases

Need to change

Takes longer

Easy reporting

Image processing

Data flow

Longer to load

Sales force

Number of tools

Easy to learn

Easy to use

Data sets

Makes creating

Earlier versions

Friendly gui

Programming background

Processing speed

Tree structure

Time series

Home

Predictive Analytics Software

We use it for analytics, and rough end extracts. This gives our staff administrative permissions to handle inside their SAS workflows, adding external data, and retaining repeatable steps to generate the same extract. We have both PC and Server SAS. My team uses the server a lot to handle larger analytical jobs. It is also used to handle data statistics and verify data quality.

Flexible to data sources
Works well across teams
Helps with SQL code writing

Difficult to write quickly, particularly if you need to change something in the data flow
Lots of clicking, slow to develop
Doesn't view data on the fly, hard to see what impact a particular change might have
Lots of licensing costs, very costly for what it does, basically equivalent to Pandas, but with huge cost tag

Integrates IT development with analytical/business areas by giving a "code share"
Visual of data flow helps communicate process to others
Reasonably shares programs with team mates

IBM Watson Studio (formerly IBM Data Science Experience), TIBCO Data Science (including Team Studio and Statistica), IBM SPSS Modeler

It is used in my current project in which I use SAS9.4 and the business problem is related to the churning of customers from retail stores. For that, I use this tool to draw some inferences. Inbuilt procedures give it a lot of power by which work becomes very easy. It is used in all of the departments and as per the client requirements.

It can load a huge amount of data as compared to R Studio and Excel.
Data processing speed is very fast, millions of records are loaded into this software very easily and data manipulation is also very easy.
Inbuilt Statistical functions and procedures make it very comfortable to use for non analytics professionals as well.

It is a costly software to use as compared to R studio and Python which are free for users.
No addition to the packages that are currently required for Image processing etc.
It is just a tool that is used for data cleaning or data manipulation or to draw statistical output. I think a number of tools are doing the same. No new changes that I have seen to it from the last 3-4 years.
Data visualization charts are not that good using the tool.

SAS EG has improved the overall efficiency as data processing is very fast and the results are highly accurate.
It's one license cost is much more than the salary of some of the employees here and it takes a few months to recover that cost.
Overall profit has increased as people learn it very fast and start deploying the work very easily.

RStudio, Microsoft SQL Server, Tableau Desktop

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 &amp; 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).

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.

Product Features
Product Usability
Prior Experience with the Product

The choice would be SAS Enterprise Guide only until a better product (rather, suite) replaces it in performance &amp; cost both.

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.

SAS Enterprise Guide is used in several business units including marketing, HR, risk (all units). At a high level, it is used for data preparation for analytics developments (models, segmentation, forecasting, ...) and also for ad-hoc queries and data exploration. Being a 4th level programing language, a lot of business users like it. It is somewhat easy and quick to learn. SAS/Enterprise guide brings that ease at the next level with lots of built-in tasks that can be used instead of code.
So in terms of business problems, let's say that SAS/Enterprise Guide is a tool to answer business questions whichever they are.

Get detailed information about a datasource quickly with built in statistical tasks.
Join data from different of different nature from multiple sources (provided you have the associated SAS/Access component).
Structure projects with a visual interface and allow dependencies between them. Easy to structure and maintain.

I would like to see advance interactions with external databases to be able to kill ongoing queries from SAS. As of now, you can stop pretty much any ongoing process besides the one running on a remote database (killing SAS/EG doesn't stop the remote process)
When creating prompts for programs, it would be nice to be able to have conditional prompts (based on the selection of other prompts). The prompts are clearly a recent feature and constantly under development but I wish it would be more powerful.
More of a SAS metadata issue but when loading SAS/EG (first connection to the server), it takes a few seconds which feels like a long time. I really don't understand why the initialization of the session can take so long. Don't get me wrong, this has no real impact on productivity but that 10s delay just feels really like eternity when you want to run some code in a new session.

Positive (cost): SAS made a bundle that include unlimited usage of SAS/Enterprise Guide with a server solution. That by itself made the company save a lot of money by not having to pay individual licences anymore.
Positive (insight): Data analysts in business units often need to crunch data and they don't have access to ETL tools to do it. Having access to SAS/EG gives them that power.
Positive (time to market): Having the users develop components with SAS/EG allows for easier integration in a production environment (SAS batch job) as no code rework is required.

SAS Enterprise Guide is used by analysts in our unit to generate reports and clean data. It is used to perform analysis on large datasets and to combine data from multiple sources.

Map out process used to clean data and generate reports
Integrate with base SAS
GUI format is easy to use

Price
Getting started using this software can be intimidating

SAS Enterprise Guide

Overview

What is SAS Enterprise Guide?