Coalesce 2022 Replay Tracks: Building the Business Case
Current economic uncertainty makes navigating new investments a little tricky. Is now the right time to consider new tooling and frameworks? Is doing more with less a solution or recipe for burnout? What data projects most clearly map to near-term business gain? If you’re looking for the Coalesce talks that attempt to answer these questions, this is the replay track for you.
Module 1: The Case for Refactoring your Team (1 hr 46 mins)
Changing the operational structure of your data team may not always require a direct financial investment, but it is an investment of time and attention—which comes at the cost of temporarily de-prioritizing other data use cases. The below might help you make the case for hitting pause on pipeline to rethink your approach for mid- to long-term gain.
- The Return on Analytics Engineering (23 mins)
- Efficient is the new sexy — A minimalist approach to growth (30 mins)
- Know your worth: Unpacking business value delivered by data teams (25 mins)
- Data teams vs the recession (28 mins)
Looking for more help? Try these additional resources:
- Analytics Engineering Everywhere - Why in the Next Five Years Every Organization Will Adopt Analytics Engineering, Jason Ganz, dbt Labs
- C-level buy-In - How to prove the value of your data team, Sylvain Giuliani, Census
- Analytics engineering vs Data Engineering- How each drives more value in the other, Alex Dovenmuehle, Big Time Data
- Building the Business Case for dbt Cloud - For those looking to make a financial case for dbt Cloud
Module 2: Product, Sales, and Finance Use Cases (2 hrs 9 mins)
A major theme across Coalesce talk submissions this year was the importance of mapping data team contributions to business value, using language and metrics familiar to the rest of the business. These talks focused on how to power product, sales, and financial use cases using analytics engineering best practices.
- Building turnkey dashboards for core financial metrics with dbt: A Little Modeling Goes a Long Way (28 mins)
- How entity modeling expedites product led growth(27 mins)
- Data automation with dollars on the line: Forecasting 7-figure deals with Hex, dbt & Hightouch (19 mins)
- What does analytics engineering have to do with product experimentation? (31 mins)
- Data as a Product: How dbt powers Slido’s Data API (24 mins)
Looking for more help? Try these additional resources
- Leverage Accounting Principles when Modeling Financial Data, Joe Markiewicz, Fivetran
- The JaffleGaggle Story: Data Modeling for a Customer 360 View, Donny Flynn, Census
- How dbt Labs manages OKRs, Erica Louie + Kira Furuichi, dbt Labs
Module 3: Getting more out of your current stack (2 hrs 25 mins)
When budgets are tight and change feels like an uphill battle, focusing on optimizing what you already have can still pay dividends. These talks focus on hidden warehouse costs and value, and the multiplying effect of cross-tool metadata and metrics.
- More metadata, less problems (31 mins)
- Beyond the buzz: 20 real metadata use cases in 20 minutes with Atlan and dbt Labs (31 mins)
- Data Apps in the Real World: How to Capture Value Locked in the Data Warehouse (29 mins)
- Extend the runway: A deep dive into data warehouse costs (31 mins)
- Why Metrics Are Even More Valuable Than You Think They Are (23 mins)
Looking for more help? Try these additional resources
- How to increase the ROI of your data stack, AirOps
- Optimize your cloud data cost: 4 steps to reduce cloud data platform cost before they control you, Sonny Rivera, Thoughtspot
- What wasting data engineering talent really costs you, GBI News
For even more Coalesce talks, be sure to check out the dbt YouTube channel
Last modified on: Sep 25, 2023
