Vinoo Ganesh

Tell us about your background Throughout my career, I have dedicated myself to creating tools, products, and technologies that help people effectively utilize their data. My passion lies in developing products that enable users to efficiently and scalably gain maximum value from their data. My journey in understanding the intricacies of data and its potential began at Palantir Technologies, where I began working on search and indexing products. As data volumes grew, I focused my efforts on solving some of Palantir customer’s core problems across the financial and defense verticals before leading customer focused compute teams.

Are you looking for a better—and easier—way to manage SQL code? In this course, instructor Vinoo Ganesh shows you how to use dbt (data build tool) to operationalize SQL in powerful ways and make the process of transforming data simpler and faster. In each chapter, Vinoo presents a real-world situation or problem, and provides focused code examples explaining how to solve the problem. He shows you how to design and implement dbt models to solve basic and advanced challenges, covering topics like schema design, generating SQL model files, table materializations, implementing CTEs, and SQL unit tests.

In this course, instructor Vinoo Ganesh gives you an overview of the fundamental skills you need to become a data engineer. Learn how to solve complex data problems in a scalable, concrete way. Explore the core principles of the data engineer toolkit—including ELT, OLTP/OLAP, orchestration, DAGs, and more—as well as how to set up a local Apache Airflow deployment and full-scale data engineering ETL pipeline. Along the way, Vinoo helps you boost your technical skill set using real-world, hands-on scenarios.

This week on The Data Stack Show, Eric and Kostas chat with Vinoo Ganesh. During the episode, Vinoo discusses how to benchmark cost, optimize your workloads, and Bluesky’s role in addressing your Snowflake bills. Video Link https://datastackshow.com/podcast/optimizing-query-workloads-and-your-snowflake-bill-with-vinoo-ganesh-of-bluesky-data/

The data pipeline has become a fundamental component of the data science, data analyst, and data engineering workflow. Pipelines serve as the glue that links together various components of the data cleansing, data validation, and data transformation process. However, despite its importance to the data ecosystem, constructing the optimal data pipeline is generally an afterthought - if it’s considered at all. This makes any changes to the central pipeline highly error-prone and cumbersome.