A Senior Business Analyst, an Analytics Engineer, and a Data Quality Engineer walk into the office. All three of them ask for dbt. Why? Join Coco Haury (WEX, Inc.) to hear about the universal appeal of dbt to folks outside traditional data engineer and analyst roles, and how dbt has helped WEX modernize their entire enterprise data platform.

Check the slides here: https://docs.google.com/presentation/d/1XNphR_il_3SGy9dU7G7PxmVoCXCCWBuFMvZYESN6KgE/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Everyone is talking about data lineage these days, and for a good reason. Data lineage helps ensure better data quality across your modern data stack. But not everyone speaks the same lineage language. Data engineers use lineage for impact and root cause analysis. Analysts and Analytics engineers use lineage to trace jobs and transformations in their warehouses. And consumers use lineage to understand why data never reached their expected destination. This results in a narrow, siloed view lineage in which only one group benefits. It’s time to stop using siloed lineage views for pretty graphs and start using end-to-end lineage to drive focused actions. In the talk, you will learn:

• How data quality tailors to specific needs of data engineers, analysts, & consumers

• How data lineage should drive actions

• A real-world example of end-to-end data lineage with Airflow, dbt, Spark, and Redshift

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

When Prateek Chawla, founding engineer, joined Monte Carlo in 2019, he was responsible for spinning up our data platform from scratch. He was more of a backend/cloud engineer, but like with any startup had to wear many hats, so got the opportunity to play the role of data engineer too. In this talk, we’ll walk through how we spun up Monte Calro’s data stack with Snowflake, Looker, and dbt, touching on how and why we implemented dbt (and later, dbt Cloud), key use cases, and handy tricks for integrating dbt with other popular tools, like Airflow, and Spark. We’ll discuss what worked, what didn’t work, and other lessons learned along the way, as well as share how our data stack evolved over time to scale to meet the demands of our growing startup. We’ll also touch on a very critical component of the dbt value proposition, data quality testing, and discuss some of our favorite tests and what we’ve done to automate and integrate them with other elements of our stack.

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

In this session participants will learn:

1. How a product analytics platform can help you understand User Flows — how users are flowing in and out of certain features.

2. The impacts that certain features can have on engagement and retention. - Understanding User and Product-Feature Usage Patterns - Quantify Impact on User Engagement - Quantify Impact on User Retention

3. Prioritize Roadmap Features Using Data Insights

4. Ensure insight fidelity and compliance with data quality and privacy tools that a PM can use

5. Increase product adoption by activating user behavior data

Check the slides here: https://docs.google.com/presentation/d/1G6qIbWkzMp_IXACvuJw1oBb46BjbV7_jCeWk5P6rOlk/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

How do you support exponentially growing companies without breaking as a data team? The answer is increasing your leverage with tools and processes. This session centers around four principles to achieve this goal: 1. don’t reinvent the wheel, 2. make your own job easier, 3. save time for innovation, and 4. invest in onboarding.

First, the first data leader at Vendr, the SaaS buying platform with customers like GitLab, Brex, and The Washington Post, will share his learnings on building a stack and team that scaled as the company grew 10x from 30 to 300 employees in under two years.

Second, we’ll give a demo of how Metaplane pulls lineage and metadata from a modern data stack that is centered around dbt. By the end of the demo, you’ll know how to setup tests, extract lineage throughout your data stack, and triage data quality alerts.More details coming soon!

Check the slides here: https://docs.google.com/presentation/d/15dQJIGeGhG0WGO6MLXtxWhmf8neY-u0c8ZLRG9GJB-s/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Building data pipelines is difficult—and adding a data governance and observability framework doesn’t make it any easier. But that was the task ahead for Deepak Konidena during his early days at Zillow. In this session, he’ll share how the platform they build on top of dbt, Airflow, Spark, and Kubernetes—ZSQL—eliminated the need for internal data teams to build their own DAGs, models, schemas and lineage from scratch, while also providing an easy way to enforce data quality, monitor changes, and alert on disruptions.

Check the slides here: https://docs.google.com/presentation/d/18HEil3_nXD8nYBhcg4m-Kpy8I8Na6MXI/edit?usp=sharing&ouid=110293204340061069659&rtpof=true&sd=true

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Pulling data directly out of application databases is commonplace in the MDS, but also risky. Apps change quickly, and application teams might update database schemas in unexpected ways, leading to pipeline failures, data quality issues, data delivery slow-downs. There is a better way. In his session, Charlie Summers (Merit) describes how their organization transforms application event streams into analytics-ready tables, more resilient to event scheme changes.

Check the slides here:https://docs.google.com/presentation/d/1K5PcoVshiHKZs_xI3K4P5JRNYTkbmnQJPMl8NmBlGfo/edit

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.