Canva is growing fast, and with that comes a much higher volume and variety of data. In conjunction with this, Canva's data specialty teams are growing too. In this video, Jose and Krishna will share how they addressed the challenges that come about with growth, the missteps, the course corrections, and what they have planned next.

Speakers: Krishna Naidu, Data Engineer with Canva Jose Galarza, Data Warehouse Lead with Canva

Dimensional modeling described in the Kimball Toolbook was in its 3rd edition 15 years ago yet is still the latest in data modeling advice. So much is different in cloud warehouses that many of those best practices are now bad practices. In this video Dave Fowler, the founder of Chartio and author of Cloud Data Management goes over what no longer applies, and what does.

Almost all of us are using our data warehouse to power our business intelligence, what if we could use data warehouses do even more?

What if we could use data warehouses to power internal tooling, machine learning, behavioral analytics, or even customer-facing products?

Is this a future we're heading for, and if so, how do we get there?

In this video, you'll join a discussion with speakers: - Boris Jabes, CEO of Census - Jeremy Levy, CEO of Indicative - Arjun Narayan, CEO of Materialize - Jennifer Li, Partner at a16z as moderator

Learn more about the speakers and their companies at: https://www.getcensus.com/ https://www.indicative.com/ https://materialize.com/ https://a16z.com/

Learn more about dbt at: https://getdbt.com https://twitter.com/getdbt

Learn more about Fishtown Analytics at: https://fishtownanalytics.com https://twitter.com/fishtowndata https://www.linkedin.com/company/fishtown-analytics/

You probably have customer data in your data warehouse — it's a must-have for understanding a business.

This data very likely includes personally identifiable information (PII) which shouldn't be shared with the entire organization.

How do you protect that data and make sure only authorized employees can see that sensitive information?

In this video, you'll learn from Ashley Van Name how JetBlue approaches data protection, particularly the problem of masking PII at scale by leveraging Snowflake's data masking features straight from their dbt project.

Learn more about dbt at: https://getdbt.com https://twitter.com/getdbt

Learn more about Fishtown Analytics at: https://fishtownanalytics.com https://twitter.com/fishtowndata https://www.linkedin.com/company/fishtown-analytics/

What does a data-driven airline look like? How does a data-driven airline behave and treat customers?

JetBlue believes a data-driven airline should: - Offer personalized customer interactions - Predict delays and other "irregular" operations - Enable all analysts to easily access a variety of data sources - Study and monitor operations in real-time to make smarter decisions

The big question is... how does an airline become more data driven?

In this video, Ashley Van Name shares how a small team of data engineers at JetBlue successfully migrated their entire data warehouse workload to dbt and shares tips for setting yourself up for success with dbt.

Fun fact about JetBlue's dbt project — they have 1800 data models, on top of 280 data sources, have defined 8500 tests and they built their entire dbt project in six months!

Learn more about dbt at: https://getdbt.com https://twitter.com/getdbt

Learn more about Fishtown Analytics at: https://fishtownanalytics.com https://twitter.com/fishtowndata https://www.linkedin.com/company/fishtown-analytics/