SQL can be used with SAS. We also use Microsoft SQLs, which I still use on occasion. Part of the background is that the coding can be done using SQL. SAS allows you to write SCL statements and is mostly drag and drop, similar to Microsoft Access.

That is the SAS Enterprise Guide's drag-and-drop functionality.

The primary use case for this solution is data searching, modeling, data insights, and analysis.

SAS Enterprise Guide is an Oracle tool that you use to query databases. The government health agency I work for only allows me to use SAS. We have about 200 users.

I am using the solution for programming, data manipulation, and query building.

Mostly accessing medical claims data from mainframe warehouses, plus occasional spreadsheets, etc. Aggregating and scoring according to specified algorithms and identifying medical practitioners who are statistical outliers with respect to certain procedures.

Loading results of these analyses into Microsoft SQL Server and writing queries for access by users without SAS licenses.

Running SAS EG on a networked Windows PC, connected to a SAS Grid on a Unix network, accessing data warehouses in Teradata.

We are using it for data cleaning and data lookups.

We use SAS Enterprise Guide for ETL and data processing.

We use it as a comprehensive data analytics and modeling process within the banking sector. It streamlines our workflow involving multiple steps, from data extraction to modeling, and it is aimed at improving various aspects of banking operations, including customer retention and risk management.

Our primary use case for the solution is creating views and filters, and we deploy the solution on-premises.

We use Tableau for visualization and SAS EG for analysis. SAS EG is more useful for analysis, while Tableau is better for visualization.

I am currently using this solution for testing purposes. I am working for a pharmaceutical company in Belgium, and we are building a data warehouse by using SAS Data Integration Studio, and we are using SAS Enterprise Guide to test our development. We are building Enterprise Guide projects by using query builder, filters, and other things. We have also built stored procedures. Sometimes, we also write SAS base code to perform unit tests after development and to do some sanity checks to respond to UAT questions. Overall, we are using the majority of functionalities of SAS Enterprise Guide. 

We use this solution for data manipulation and statistics.

We primarily use the product for data analysis and investigations.  

I use it for programming. When we import data sets or databases, we work with data management and program scripts, etc. We have its basic license.

Using with SAS Grid, data manipulation, preparation, and modeling development.

We use SAS EG to manipulate large datasets and prepare them for actuarial analysis with other programs, as well as ad hoc analysis.

Our primary use case is to analyze the sales data of our company. We have an in-house database that has all data relating to our agents and our production. I use it when I want to have a quick check on the data. I'm the finance system and process senior manager in the company.

We use this solution for moving users that need statistical data analysis and data transformation functionality that do NOT have a background in programming and/or SQL to a tool that allows for some degree of self-service. It also provides access to data sources (databases that require administrative access) that do not support individual user access.

Everyday use for application development (reporting, data analysis, scoring, and ETL). 

I use it for quality assurance and identification of outliers. EG is great for a quick standardized sort of analysis.

SAS EG is an excellent tool for data manipulation and analysis.

We make the most use of scheduled processing with Base SAS. If there is an error in one process, the others do not run as well because of possibly one error. Therefore, we now mostly use the Enterprise Guide for such scheduling purposes, so error processes will not inhibit the others.

• Data preparation
• Statistics.