An Easy Approach to ETL with Apache Spark - Visually prepare, integrate, and transform data as it arrives

Executing analytical queries on massive data volumes with traditional databases and batch ETL processes is complex, expensive, and time-consuming.

Open-source distributed computing technologies like Apache Spark and Hadoop provide an efficient and cost-effective data processing paradigm. Apache Spark enables end-to-end ETL workflows for incessant data streaming from heterogeneous sources and overcomes the constraints imposed by legacy ETL processes. Explore how Apache Spark provides a powerful and efficient approach to ETL. Join our upcoming webinar where experts at Impetus talk about:

• A modern approach to ETL
• Advantages of choosing Apache Spark to transform legacy ETL processes
• Easy adoption and integration of Spark based ETL
• Writing production grade Spark ETL jobs visually
• Deploying applications on-premise and in the cloud

Speakers:

Saurabh Dutta

Senior Solutions Architect, Impetus StreamAnalytix

Aman Solanki

Senior Product Engineer, StreamAnalytix