Simplifying Data Management through Metadata Integrations and AI Infusion – Kevin Shen, IBM

Simplifying Data Management through Metadata Integrations and AI Infusion – Kevin Shen, IBM

In this demo we’ll go through two key pieces of watsonx.data, IBM’s new Data Lakehouse offering. Multiple analytics engines working on the same data: – Demo: Multiple engines working on the same data set so you can use the analytics tools you love without having to deal with the ugly plumbing Semantic Automation: Leverage AI to simplify data discovery and manipulation, allowing your data to work for you – Demo: Using a chat interface to find tables of relevance and how AI can enrich data sets with semantic information

Using Presto’s BigQuery Connector for Better Performance and Ad-hoc Query connector for better performance and ad-hoc query in the Cloud – George Wang & Roderick Yao

Using Presto’s BigQuery Connector for Better Performance and Ad-hoc Query connector for better performance and ad-hoc query in the Cloud – George Wang & Roderick Yao

The Google BigQuery connector gives users the ability to query tables in the BigQuery service, Google Cloud’s fully managed data warehouse. In this presentation, we’ll discuss the BigQuery Connector plugin for Presto which uses the BigQuery Storage API to stream data in parallel, allowing users to query from BigQuery tables via gPRC to achieve a better read performance. We’ll also discuss how the connector enables interactive ad-hoc query to join data across distributed systems for data lake analytics.