Streaming Data: The Nexus of Cloud-Modernized Analytics
Leveraging business data as a valuable asset is no longer a debated concept – it’s a broadly adopted, competitive undertaking that’s part and parcel to cloud modernization. Today, if there’s one thing that defines competitive advantage in the data analytics arena it’s streaming data platforms. Older approaches employing batch-only analytics, brittle ETL pipelines, and the latency they can introduce just don’t cut it anymore. Cloud-Modernized Analytics are poised to step in and take over.
Whether for on-demand movement and processing of data or real-time analytics, a rock-steady streaming platform is essential to doing analytics right. Such platforms help with transactional data too, enabling it to stream from the line-of-business applications where it’s born, directly into data warehouses and data lakes, in real-time. Today – especially in the context of digital transformation and operational intelligence – it’s stream or go home.
Join us for a dynamic conversation on these topics and more in this free 1-hour webinar from GigaOm Research: “Streaming Data: The Nexus of Cloud-Modernized Analytics”. The Webinar features GigaOm analyst Andrew Brust and special guest, Steve Wilkes, co-founder and CTO of Striim, a leader in continuous data streaming, across the data center, and the cloud.
In this 1-hour webinar, you will discover:
- The main components of a streaming platform: Ingestion, processing and delivery
- How streaming data integration supports cloud adoption and building new apps in the cloud
- How streaming data architecture accelerates AI/ML initiatives
- Why the Internet of Things (IoT) ties into streaming data, yet doesn’t define it
- How change data capture (CDC) technology bridges the worlds of streaming and transactional data for analytics
Register now to join GigaOm and Striim for this free expert webinar: “Streaming Data: The Nexus of Cloud-Modernized Analytics”.
Who Should Attend:
- Chief Data Officers
- Chief Analytics Officers
- Digital Transformation leaders and specialists
- Data Engineers
- Data Scientists
- Cloud Architects