Today, businesses need to leverage massive volumes of data in order to quickly derive actionable insights. The challenge is that data tends to reside across multiple disparate systems and services either on-premise and/or in the cloud, yet it needs to be combined in ways that make sense for deep analysis. The goal is to centralise this data, a single source of truth is essential to accuracy and in shaping a 360 degree perspective of the businesses. Data flow itself can be especially unreliable as there are many points, during transit from one system to another, where corruption or bottlenecks can occur. The scale and impact of this challenge is only magnified due to the ever increasing breadth and scope of the role that data continues to play.

This is why data pipelines are critical since they eliminate many manual steps in the process, enabling a smooth, automated flow of data from one location to another. Data pipelines are also important for real-time analytics to help organisations make decisions faster, through actionable data-driven insights.In this session, we will discuss and demonstrate how Snowflake’s native features; Auto-Ingest (through Snowpipe), Streams and Tasks can provide customers with continuous, automated and cost-effective services to load data simply and efficiently.

In this session, we will discuss and demonstrate how Snowflake’s native features; Auto-Ingest (through Snowpipe), Streams and Tasks can provide customers with continuous, automated and cost-effective services to load data simply and efficiently.