In this talk, we will discuss how we use Unified Monitoring to help provide centralized monitoring of all deployed data analytics solutions in our Data Science Platforms, Self-Service Analytics Platforms and MLOps.
- What Platforms metrics and insights supported?
- What we need to prepare to support the numerous data science and analytics platforms to monitor and how we integrate it?
- How can we monitor the Machine Learning Model job submission?
Seah Boon Keong (PhD) – D&A, Head of Data Science Platform | Digital Business Solutions | BAT | Malaysia
I lead the Data Science Enablement team at Data and Analytics of BAT. The Data Science Enablement team consist of Data Science Engineering team looking at MLOps area, AzureML and Azure Databricks enablement. In addition, the Self-Service Analytics area help supports the PowerBI, MicroStrategy and Dataiku enablement. The work we do covers MLOps, metrics, and insights for monitoring of all Data Science and Self-Service Analytics platforms, automation, and reusability using MLOps, DevOps, RPA and Infrastructure as Code, ServiceNow and NewRelic integration to help solve data science engineering challenges across multiple data science platforms.
Seah Boon Keong (PhD) – D&A – Head of Data Science Platform | Digital Business Solutions | BAT | Malaysia