Planning your Next-Gen Change Data Capture (CDC) Architecture in 2019
Dec 19, 2018 | 10:00 am PT / 1:00 pm ET
Traditional databases and batch ETL operations have not been able to serve the growing data volumes and the need for fast and continuous data processing.
How can modern enterprises provide their business users real-time access to the most up-to-date and complete data?
In our upcoming webinar, our experts will talk about how real-time CDC improves data availability and fast data processing through incremental updates in the big data lake, without modifying or slowing down source systems. Join this session to learn:
- What is CDC and how it impacts business
- The various methods for CDC in the enterprise data warehouse
- The key factors to consider while building a next-gen CDC architecture:
- Batch vs. real-time approaches
- Moving from just capturing and storing, to capturing enriching, transforming, and storing
- Avoiding stopgap silos to state-through processing
- Implementation of CDC through a live demo and use-case
Saurabh is a Technical Product Manager at StreamAnalytix where he leads multiple engineering and R&D efforts. He is one of the early team members who bootstrapped StreamAnalytix. He is responsible for analyzing complex engineering and business challenges for clients, managing and developing a roadmap and providing an appropriate solution which can be incorporated in the product. He brings a unique blend of business acumen and technical knowledge that help clients achieve their objectives. His areas of expertise include big data, advanced analytics and cloud computing.
Sameer is a Senior Solutions Architect at StreamAnalytix where he leads the product engineering efforts. He is responsible for analyzing complex engineering and business challenges to devise appropriate solutions. His areas of expertise include big data, cloud computing, and advanced analytics.
An Easy Approach to ETL with Apache Spark – Visually prepare, integrate, and transform data as it arrives
2019-03-08 23:30:00 - 10:00 am PT / 1:00 pm ET