Join the data engineering community on June 14th and hear two more stories of end-user experiences with dbt. We will predominantly focus on people's experience with dbt, but will also discuss broader topics related to data teams, such as data stacks, data ops, modeling, testing, and team structures.
A big thank you to our friends at Upsolver for sponsoring this event!
Empower Datamesh with dbt: Streamlining workflows and promoting cross-team collaboration
William Kuan, Senior Data Engineer, Rapid7
I'll explore the benefits of using dbt in a decentralized approach to managing analytical data in complex and large-scale environments. By distributing data responsibility to those closest to it, this approach encourages agility, innovation, and accountability. With a decentralized platform in dbt, teams can collaborate, self-serve, and work in parallel, leading to more efficient achievement of data-driven goals. This approach empowers teams to take ownership of their data and work with it in a way that suits them, while also facilitating cross-team collaboration and simplifying CICD and workflows.
Using dbt to optimize queries from your phone
Sabin Thomas, Founder & CTO, Zing Data
Data analysis tools have traditionally been built for desktops and for power users. The team at Zing Data believes in data interactivity that has been built for the masses - that is mobile-first, simple, collaborative and ubiquitous. In this session we'll go over architecture patterns for this next-gen of tooling, and the difference in needs for emerging market users for data products. I will also examine using dbt to evaluate SQL query composition patterns and how Zing Data has evolved these patterns to account for mobile first problems - poor connectivity, long running queries, push notifications, location-sensitive query composition and others.
To attend, please read the Required Participation Language for In-Person Events with dbt Labs: https://bit.ly/3QIJXFb
➡️ Join the dbt Slack community: https://www.getdbt.com/community/
🤝For the best Meetup experience, make sure to join the #local-boston channel in dbt Slack (https://slack.getdbt.com/).
dbt is a data transformation framework that lets analysts and engineers collaborate using their shared knowledge of SQL. Through the application of software engineering best practices like modularity, version control, testing, and documentation, dbt’s analytics engineering workflow helps teams work more efficiently to produce data the entire organization can trust.
Learn more: https://www.getdbt.com/