

SAS Data Management and Qlik Compose compete in the data management and data integration category. SAS Data Management seems to have the upper hand with its robust data management capabilities across diverse environments, although Qlik Compose shines in simplifying data warehouse automation.
Features: SAS Data Management offers capabilities like ETL, CDC, and MDM, delivering comprehensive data integration and analysis, praised for its flexibility and powerful analytics abilities. Qlik Compose is known for its simplicity in data warehouse automation, real-time replication, and excellent auto-mapping, making data modeling and code generation easy.
Room for Improvement: SAS Data Management could benefit from more competitive pricing and licensing, enhanced cloud integration with better connectivity options, and improved documentation. Qlik Compose faces challenges with complex SQL processing, needs better monitoring and ETL capabilities, and calls for improved support for high-volume data processing.
Ease of Deployment and Customer Service: SAS Data Management is mostly deployed on-premises, with strong post-acquisition customer service, but technical support experiences vary. Qlik Compose offers flexible deployment options on-premises and cloud, receiving feedback for decent but improvable customer support.
Pricing and ROI: SAS Data Management is considered expensive but valued for its comprehensive capabilities that offer high ROI for large enterprises. Qlik Compose offers a pricing model based on data volume with mixed feedback, showing potential ROI by optimizing data accuracy and efficiency, but its competitiveness for broader adoption could improve.
| Product | Mindshare (%) |
|---|---|
| SAS Data Management | 1.3% |
| Qlik Compose | 0.9% |
| Other | 97.8% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 3 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.
Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.
What are the key features of Qlik Compose?In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.
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.
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