Legacy data infrastructure was slowing down Nearmap’s data team: time-consuming maintenance, slow analytical queries and full model rebuilds that took up to two days to complete!
Join Jonathan Mak, to learn why Nearmap adopted a modern analytics engineering workflow using dbt, and see how Snowflake has proven to be the best cloud data platform to support that workflow.
This live webinar and Q&A will cover:
- Empowering data analysts: How dbt’s SQL-based, in-warehouse transformation coupled with Snowflake’s effortless scalability eliminated the data engineering bottleneck.
- Decreasing data engineering costs: How Snowflake freed Nearmap from vacuuming, node changes, indexing, and other time-consuming data engineering work.
- Building more flexible data models: Better query performance eliminated the need for data aggregation, allowing the team to build richer, more flexible data models that still performed beautifully in Looker.
- Live Demo: dbt + Snowflake
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