What do you do if your confidence in Data Warehousing is shaken by setbacks?

If your confidence in a 40-year-old technology is shaken by setbacks, then there is a fundamental gap in the perception of reality that has to be recognized before any future progress is possible. Data Warehousing today is about as mature as technology gets these days. So, the probability of a setback caused by the technology itself is close to zero. If there is a setback, it is most likely the result of not using the right tool for the job, not having the skill to use the tool, or having to deal with the chaos of running a project in a modern corporate environment that has nothing to do with technology per se. So, there are just two questions to be answered: is it time to skill up, or is it time to find a better company to work for?

When the tempest of setbacks churns the waters of your data warehousing journey, fear not, weary traveler. Here’s how to mend your sails and navigate onward: Acknowledge the Storms: Face the waves: It’s okay to feel shaken. Acknowledge the setbacks, but don’t let them capsize your resolve. Remember resilience: Every seasoned sailor has weathered storms. You’re no exception. Analyze the Compass: Root cause analysis: Dive deep into the setbacks. Understand what went awry. Was it a faulty query, a schema mishap, or a resource bottleneck? Learn from shipwrecks: Failure is a compass. It points you toward growth. Chart a New Course: Course correction: Adjust your trajectory. Maybe it’s time to explore a different data model, switch tools

Remain flexible and open to adjusting your goals and strategies as needed based on evolving circumstances or new information.

Sometimes, it can be hard to hear feedback, especially if it points out areas where you could improve. However, being open to constructive criticism is essential for growth. Embrace feedback as an opportunity to learn and develop your skills further.

That's alright if one feels less confident about their data warehousing knowledge since it is very conceptual and mostly done by data architects while modelling. But Anybody can start with getting all the theoretical understanding clear and then get into waters. Take a small dataset and try to build a small data warehouse. Do SCD on it. You will touch and walk through so many tools or just python code but concepts remain the same hence emphasis on concepts. It's easier and more fun than you think trust me you have already got it.Go build that data warehouse. Storage S3/blob/database -- {data lake } -- ELT(tools , code ) -- Data Warehouse

Theory is important, but practical experience is invaluable. Look for opportunities to apply your knowledge and skills in real-world scenarios through hands-on projects, internships, or side projects.

Recognize and celebrate milestones and achievements as you progress through the implementation process. Address any concerns or questions proactively to foster buy-in and collaboration.

Create forums for team members to discuss successes, failures, and lessons learned, and facilitate knowledge sharing and collaboration.

Incorporate regular breaks into your workday to prevent burnout and maintain focus and productivity. Whether it's a short walk, a coffee break, or simply stepping away from your desk for a few minutes, giving yourself time to recharge can significantly improve your overall well-being and performance.

To regain the trust in the Data Warehouse, follow these steps 1- Analyze the specific issues or setbacks that have occurred. Understand whether they are related to data quality, performance, usability, or any other aspect of DWH 2- Communicate with stakeholders who rely on the data warehouse. Share your concerns and explain the setbacks. 3- Perform a comprehensive review of the data warehouse architecture, processes, and best practices. Identify any gaps, weaknesses, or areas for improvement. 4- Implement necessary improvements and changes to DWH. 5- Establish clear ownership and accountability for data quality and integrity. 6- Finally Set up monitoring mechanisms to proactively detect and address any issues that may arise in the future.

Reflect carefully on what went wrong without self-blame. Look for lessons from experts. Refresh your skills with online training to address weaknesses. Start small on a proof-of-concept project designed for success to rebuild momentum. Stay focused on business goals, not just technology. Collaborate closely with stakeholders for diverse feedback before proceeding. Remember all projects evolve through learning. Setbacks are stepping stones to get stronger. Believe in data warehousing's long-term potential with reflection, skills growth and partnership over time. Confidence returns as you grow from mistakes. Keep focused on lessons, not faults, through expert guidance and self-improvement.