SAS Data Management vs. dbt
A side-by-side comparison based on G2 review data.
| Metric | SAS Data Management | dbt |
|---|---|---|
| Overall rating | 4.1 | 4.7 |
| Review count | 100 | 209 |
| Ease of use | 7.7 | 9.1 |
| Ease of setup | 8.7 | 8.8 |
| Quality of support | 8.2 | 9.0 |
| Meets requirements | 8.6 | 9.3 |
| NPS | 35.051546 | 81.25 |
| Small Business | 26.0% | 27.1% |
| Mid-Market | 23.0% | 56.5% |
| Enterprise | 51.0% | 16.4% |
| Total page views | 93 | 780 |
| Total LLM citations | 134 | 4,329 |
SAS Data Management
SAS Data Management is a comprehensive solution designed to transform raw data into a valuable business asset by improving, integrating, managing, and governing data across an organization. It enables users to access data from various sources, create rules, collaborate with teams, and manage metadata, thereby preparing data for analytics and informed decision-making. Key Features and Functionality: - Data Access and Integration: Seamlessly access data from diverse sources, including legacy systems and modern platforms like Hadoop, ensuring comprehensive data integration.
- Ease of Use
- Analytics
- Data Quality
- Data Cleaning
- Data Management
- Data Preparation
dbt
dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.
- Ease of Use
- Features
- Automation
- Transformation
- Productivity Improvement
- Data Quality