What do you do if your data warehousing processes fail and you want to innovate and improve?

1 Identify the root cause

The first step is to identify the root cause of the failure, which can be challenging due to the complexity and interdependence of data warehousing processes. You need to use various tools and techniques, such as logs, alerts, dashboards, audits, tests, and feedback, to trace the source and impact of the failure. You also need to involve the relevant stakeholders, such as data engineers, analysts, users, and managers, to gather information and insights. By identifying the root cause, you can determine the scope and severity of the failure, as well as the best course of action to fix it.

2 Implement a solution

The next step is to implement a solution that can resolve the failure and restore the normal functioning of the data warehousing processes. Depending on the nature and urgency of the failure, you may need to apply a quick fix, such as correcting a data entry error, restarting a system, or rerunning a process, or a more comprehensive fix, such as redesigning a data model, updating a software, or migrating a data source. You need to follow the best practices and standards of data warehousing, such as data quality, security, scalability, and documentation, when implementing a solution. You also need to communicate and coordinate with the stakeholders to ensure a smooth and timely implementation.

3 Evaluate the outcome

The third step is to evaluate the outcome of the solution and measure its effectiveness and efficiency. You need to use various metrics and indicators, such as data quality, performance, usability, and satisfaction, to assess the results and benefits of the solution. You also need to compare the outcome with the baseline and the expectations, and identify any gaps or discrepancies. By evaluating the outcome, you can verify that the solution has solved the failure and improved the data warehousing processes.

4 Learn from the experience

The fourth step is to learn from the experience and extract valuable lessons and insights that can help you improve your data warehousing processes in the future. You need to conduct a post-mortem analysis and review the causes, consequences, and solutions of the failure, as well as the strengths, weaknesses, opportunities, and threats of the data warehousing processes. You also need to document and share your findings and recommendations with the stakeholders, and solicit their feedback and suggestions. By learning from the experience, you can identify the best practices and pitfalls of data warehousing, and foster a culture of continuous improvement.

5 Innovate and improve

The final step is to innovate and improve your data warehousing processes by applying the lessons and insights you learned from the experience. You need to look for ways to enhance the quality, efficiency, and value of your data warehousing processes, such as adopting new technologies, methods, or frameworks, optimizing existing processes, or creating new processes. You also need to test and validate your innovations and improvements, and monitor and adjust them as needed. By innovating and improving, you can increase the competitiveness, resilience, and relevance of your data warehousing processes.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?