Augmented Data Management & Analytics offers self-service for business users, ensuring data governance and compliance through automated tasks. Leveraging DSML models and AI, it accelerates data integration and preparation, while providing automated contextual insights and forecasts for enhanced decision-making. The platform supports citizen developers in automating data preparation, ML model creation, and deployment.

From the research I have done, here are highlighting advantages of Augmented Data Management & Analytics:

1. Self- Service Capabilities: Augmented data management & analytics empowers business users with self-service capabilities, allowing them to access and analyze data without heavy reliance on IT teams. This self-service approach promotes data democratization and agility within organizations.
2. Data Governance and Compliance: Augmented data management & analytics assists in ensuring data governance and compliance by automating data classification, data lineage, and data access controls. This helps organizations meet regulatory requirements and maintain data privacy and security.
3. Automated Data Integration & Preparation: Augmented data management & analytics allow data users to automatically integrate and prepare data prior to transformation from various sources with drag-and-drop support. It utilizes DSML models and AI to accelerate data integration, data cleaning, quality check, and metadata management.
4. Automated Contextual Insights and Forecasting: Augmented Data Management & Analytics allows data users to automatically generates insights by dynamically monitoring changes in datasets while identifying & notifying anomalies in datasets. With the integrated ABI platform the users can easily visualize insights with the help of automated data storytelling.
5. Assisted ML Model Building: Augmented data management & analytics will help citizen developers to automatically create DSML model with automated data preparation, integration, feature generation, algorithm selection through (AutoML) and automated model deployment & monitoring through (ModelOps).

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Author: Sofia Ali, Senior Analyst At Quadrant Knowledge Solutions