

WhereScape RED and SAS Data Management are both well-regarded in the data management category. WhereScape RED seems to have the upper hand for rapid development and ease of use due to its automation capabilities, whereas SAS Data Management is preferred for its comprehensive data governance features and reliability.
Features: WhereScape RED offers automation and metadata-driven development, facilitating quick data warehouse creation with drag-and-drop simplicity. It also includes automated documentation. SAS Data Management provides robust data governance and integration tools, offering a unified platform that supports data standardization and compliance.
Room for Improvement: WhereScape RED faces performance limitations with larger datasets and relies on database operations affecting scalability. Users also request better data acquisition and enhanced scheduling features. SAS Data Management is critiqued for its high cost and complexity, with suggestions for improved ease of use in data sharing and cloud integration.
Ease of Deployment and Customer Service: WhereScape RED supports both on-premises and public cloud deployments with technical support noted for its accessibility. SAS Data Management's hybrid cloud capabilities offer flexibility but can be complex to implement. It provides good customer service, though technical support experiences differ.
Pricing and ROI: WhereScape RED follows a seat-based licensing model, which is flexible and cost-effective, often leading to quicker ROI. SAS Data Management is considered expensive, justified by its extensive suite of features suitable for large enterprises focused on data governance. Both solutions offer significant ROI with WhereScape RED providing quicker time to market and SAS ensuring reliability and integration strengths.
Reliable data plus less human intervention and less error result in a strong return on investment.
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
SAS Data Management can be improved in terms of the learning curve.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
From my experience, SAS Data Management is an expensive tool.
SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
The metadata management feature of SAS Data Management helps a lot; creating your data marts or data lake with good naming conventions, library conventions, and so on is very important because it allows easy queries to find the whole structure, though I think metadata governance also depends on first definitions, not only on the tool.
| Product | Mindshare (%) |
|---|---|
| SAS Data Management | 1.2% |
| WhereScape RED | 1.3% |
| Other | 97.5% |

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 8 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 4 |
| Large Enterprise | 11 |
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
WhereScape RED streamlines data warehousing processes through automation, empowering organizations with agile code generation and easy management of data integration and documentation.
WhereScape RED provides automated documentation, agile code generation, and a metadata-driven framework, making it ideal for enterprise data warehousing. It integrates well with methodologies like Data Vault and Kimball, offering data lineage, impact analysis, and ELT capabilities. With diverse data environment support such as Teradata, Oracle, and SQL Server, it simplifies staging, transforming, and loading processes. Though some users suggest improvements in performance and multi-database support, RED stands out with its automation that enhances code readability and reduces manual tasks.
What are the most valuable features of WhereScape RED?WhereScape RED is often implemented in industries needing robust data integration solutions. It is utilized for business reporting within sectors relying on SQL Server for their ETL processes. Its drag-and-drop functionality and support for heterogeneous data sources make it a versatile tool for managing complex data environments.
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