Data engineering is all about building data pipelines for ingesting, processing, and governing all types of data (structured, unstructured, semi-structured) at all latencies (batch and streaming) in cloud environments.
Informatica offers the industry’s most comprehensive cloud data engineering portfolio that enables data engineers to discover, ingest, integrate, cleanse, prepare, and operationalize data and data pipelines to drive AI & analytics from the Microsoft Azure ecosystem. Microsoft Azure data & analytics services together with Informatica's Data Engineering portfolio - Data Engineering Integration, Data Engineering Quality, Data Engineering Streaming, Enterprise Data Preparation, and Enterprise Data Catalog - can help you drive successful next-gen analytics and AI projects in your enterprise.
In this webinar "End-to-End Data Engineering for AI & Analytics on Microsoft Azure" you will learn about:
- Data engineering integration in a Spark serverless mode for data pipelines that feed the Azure Data Lake Store (ADLS) for analytics and AI
- Data engineering streaming for real-time analytics that extend to the edge leveraging Spark Structured Streaming
- Cloud mass ingestion of all types of data en masse or in real-time into Azure ADLS
- Enterprise data preparation for data scientists and analysts to quickly find, prepare, and operationalize trusted data
- Enterprise data catalog with powerful search, data lineage, and impact analysis
- DEMO of end-to-end data engineering with Informatica on Microsoft Azure (ADLS, SQL Data Warehouse, Databricks, etc.)
If you're considering Microsoft Azure or already using Azure to drive analytics & AI, this webinar is a must-attend.
