What do you do if your data warehousing project fails and how can you turn it into a learning opportunity?

Evaluate the quality and reliability of the data used in the project, as data issues often underpin many data warehousing failures. Assess data completeness, accuracy, consistency, and timeliness to determine if data quality issues contributed to project setbacks or failures.

The initial step is to meticulously evaluate what went wrong with the project. Dive deep into the project’s lifecycle to understand the stumbling blocks encountered at each phase. Was the project scope not clearly defined? Did the technology stack fail to meet the project’s needs? Or were there gaps in communication and collaboration among team members? Identifying these root causes is fundamental to learning from the project and forms the basis for improvement in future initiatives. Approach this analysis with an objective mindset, focusing on the situation rather than placing blame on individuals.

Collecting feedback from everyone involved with the project is crucial for a well-rounded understanding of its shortcomings. Solicit insights from team members, stakeholders, and, if possible, the end-users of the data warehousing solution. This could be done through one-on-one interviews, surveys, or post-mortem meetings. Encourage honest and open communication to ensure you capture a comprehensive view of the project’s challenges. Analyzing this feedback can reveal insights into both technical issues and project management areas that need refinement.

Seek feedback from a diverse range of stakeholders, including technical experts, business users, project managers, and executive sponsors, to gain multiple perspectives on the failure.

Provide opportunities for hands-on experience and practical application of newly acquired skills through real-world projects, simulations, or sandbox environments. Encourage team members to apply their learning directly to data warehousing initiatives within the organization to reinforce concepts and build confidence. Conduct a skills assessment to identify specific areas where your team may be lacking expertise or knowledge. Prioritize training in fundamental data warehousing concepts and technologies relevant to your organization's needs and objectives.

Pilot projects provide an opportunity to test new approaches in a controlled environment and gather feedback for refinement. Provide opportunities for training, support, and collaboration to facilitate the transition to new ways of working.

Failures aren’t always technical. They can be political, related to opinion and preferences, leadership stances and ultimately fear. Actual, real-world, revenue producing apps and systems can get canned out of a misunderstanding of open source risks, job security and even the role of engineering. Doesn’t matter; get caught trying, the knowledge and experience remains with you ??