Building Real-time Trading Dashboards with Lakeflow Declarative Pipelines, Serverless OLTP and Databricks Apps

Overview
Tuesday
June 10
4:10 pm
Experience | In Person |
---|---|
Type | Breakout |
Track | Data Engineering and Streaming |
Industry | Financial Services |
Technologies | Apache Spark, DLT, Databricks Apps |
Skill Level | Intermediate |
Duration | 40 min |
Barclays Post Trade real-time trade monitoring platform was historically built on a complex set of legacy technologies including Java, Solace, and custom micro-services.This session will demonstrate how the power of Lakeflow Declarative Pipelines' new real-time mode, in conjunction with the foreach_batch_sink, can enable simple, cost-effective streaming pipelines that can load high volumes of data into Databricks new Serverless OLTP database with very low latency.Once in our OLTP database, this can be used to update real-time trading dashboards, securely hosted in Databricks Apps, with the latest stock trades - enabling better, more responsive decision-making and alerting.The session will walk-through the architecture, and demonstrate how simple it is to create and manage the pipelines and apps within the Databricks environment.
Session Speakers
Matt Slack
/Senior Specialist Solution Architect
Databricks
Matthew Moorcroft
/Specialist Solutions Architect
Databricks