What is your framework for how to think about your data and reporting stack?

When constructing and evaluating our data and reporting stack, we always try to follow a structured approach to ensure that we have a robust, scalable, and efficient system in place. Here are some of our guiding principles:

1. Define Clear Objectives:

- Understand what we want to achieve with our data and reporting. It always start here!

- Set specific goals and Key Performance Indicators (KPIs).

2. Ensure Data Quality and Integrity:

- Implement strict data governance policies.

- Regularly audit and clean data to maintain accuracy and reliability. This is the basis for adoption.

3. Seamless Data Integration:

- Ensure data can flow effortlessly between different tools and systems.

- Use integration platforms if necessary to connect disparate data sources, like Snowflake.

4. Scalability and Performance:

- Choose tools and infrastructure that can grow with our data needs.

- Ensure the system performs well, even as data volume increases.

5. User Accessibility and Adoption:

- Ensure that the tools are user-friendly and accessible to non-technical users.

- Provide training and resources to encourage widespread adoption.

- Pick power users and use them as ambassadors.

6. Actionable Reporting and Analytics:

- Focus on tools that provide clear, actionable insights.

- Ensure reports are tailored to the needs of different departments and stakeholders.

7. Feedback Loops and Continuous Improvement:

- Regularly gather feedback from users to understand their needs and challenges.

- Continuously optimize and update the stack based on user feedback and changing business needs.

8. Cost Management:

- Regularly assess the cost-effectiveness of each tool in the stack.

- Ensure we are getting value for our investment.

9. Security and Compliance:

- Implement strong security measures to protect our data.

- Ensure all tools and processes are in compliance with relevant regulations and standards.

It's a long list but there are no shortcuts I'm afraid, by adopting this framework we try to ensure that our data and reporting stack not only meets our current needs but is also poised to support our future growth and evolution.