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  • 🐳Using Whaly Guides
  • Core concepts
    • πŸ“šGetting started
      • Data stack architecture
      • Consumers vs Builders
      • Data layers in Whaly
      • License Mapping
    • πŸͺ„Data modeling
      • Understanding data models
      • Designing data models
      • Common modeling patterns
        • Event schema
      • Maintaining data models
      • Data models best practices
    • πŸ–ŒοΈExplorations
      • Understanding Explorations
      • Designing Explorations
      • Maintaining Explorations
      • Mistakes to avoid
  • Training
    • πŸ‘οΈFor viewers
    • πŸ‘©β€πŸ’»For editors
    • πŸ§™For builders
      • Setting up the training material
      • Creating a chart
      • Using and editing explorations
      • Filtering a dashboard
      • Creating explorations and models
  • Inspiration
    • πŸ—’οΈUse cases
      • Billing / Invoicing
      • Customer success
      • Fundraising
      • Marketing
      • Partnerships
      • Product
      • Sales
      • Strategy
    • πŸ’¬Communication
    • πŸ’‘Tips
  • Recipes
    • 🀝Customer care
      • How to build a 360Β° customer dashboard
    • 🏦Finance
      • Modeling your recurring revenue
        • SQL for simplified MRR calculation
        • SQL for advanced MRR calculation
    • πŸ“£Marketing
      • Track your entire Marketing Funnel
      • Calculate your Customer Acquisition Cost
      • Create a partner dashboard
    • πŸ’ΌSales
      • Analyze the impact of your Sales velocity on your closing rate
      • Create a sales performance dashboard
      • Build a target oriented sales dashboard
  • Misc
    • 🧐SQL Fanout
    • πŸ“¦Backup your data using BigQuery
    • ☁️Embedding reports in Salesforce
    • πŸ‘¨β€πŸ’»Useful SQL operations
      • Flattening categories
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  1. Inspiration

Tips

ChatGPT

Whaly users are reporting the usage of ChatGPT to help builders to generate SQL queries to build models faster in the workbench.

Some users even built a tool to feed the schema of the tables into their ChatGPT request so that ChatGPT answers are more accurate.

Data coaching

Whaly customers with a small data team (<3 people) are taking a β€œData Mentor” that give 1h per week and find it a great way to speed up the team learning and deployment of the use cases. Those mentors are helping on the tech side as they have a good knowledge of the existing tooling (dbt, SQL, …) as well as the effective processes and organisation to run a data team efficiently and maximise the impact of the Data team.

Objectives tracking

Many Whaly users are importing team and individual objectives on their charts to show the completion rate of their goal. This is helpful to set:

  • Daily/Weekly cadence objectives

  • Quarterly strategic initiative

PreviousCommunicationNextCustomer care

Last updated 1 year ago

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