Data Stacks in the Cloud
The talk has adjourned. Thanks all for your support!! Photos below.
Presented by Adam Stone, Ph.D.
Data is ever-increasing and increasingly scattered across multiple app databases and SaaS services, while business teams still expect quick answers to their data questions. Traditional databases are bursting at the seams, and running SQL scripts on these databases to extract-transform-load data & produce business metrics (KPIs) takes up more resources and time. To address these challenges, a data stack ecosystem has sprouted, centered around cloud-based data warehouses (Amazon Redshift, Snowflake, Google BigQuery). Data loaders interface with them, data transformers convert raw transactional data into analytical data using powerful cloud-based processing, and data reporters rapidly serve data to end users. Best of all, these work on a separate, brand-new layer on top of your existing database infrastructure; no Big Changes needed! I’ll give an overview of the different components in the data stack and examples why cloud-based data warehousing is the way to go.
Presented in American Sign Language (ASL). We will have an American Sign Language interpreter also available to voice and take in questions from our non-signers audience.
Kudos to Convo for allowing us to host using Zoom!
Two photos during talk:
