A continuación, le indicamos cómo puede utilizar la retroalimentación para mejorar sus habilidades profesionales de BI.

To use feedback to enhance your BI career skills: 1. Actively seek feedback from peers and supervisors to identify areas for improvement. 2. Analyze the feedback to understand specific skills or knowledge gaps. 3. Create an action plan to address the identified areas and set measurable goals. 4. Apply the feedback to your daily tasks and projects to develop and refine your skills. 5. Regularly review and adjust your action plan based on additional feedback to ensure continuous growth.

Leverage feedback to sharpen your BI career skills by actively seeking input on your work, particularly in areas like data analysis, visualization, and reporting. Use constructive criticism to identify gaps in your knowledge or approach, then target those areas for improvement through training or practice. Positive feedback helps you recognize and build on your strengths, such as advanced DAX or data storytelling. Regularly reflecting on feedback allows you to adapt to changing industry standards, refine your techniques, and position yourself as a more versatile and effective BI professional, driving your career growth.

The BI arena is sometimes a battlefield where the are many experts with different backgrounds and understanding of the business. So, at the intersection between BI and business processes there can be many sources of confusion - definition of business and technical terms, interpretation of processes, measures, etc. A data model is usually based on a set of processes, the data structures behind, definitions and other ingredients. Therefore, lot of work is based on one's understanding rooted in the information available, which might be correct or not. Yes, it's important to include feedback and consider the advices in further work, if they make sense. Unfortunately, there are also bursts of ego from other parties' side. Keep calm and breath!

Constructive criticism is a valuable tool for growth. By actively seeking and embracing feedback, I've been able to identify areas for improvement and refine my approach to problem-solving and data analysis, leading to more effective and insightful outcomes.

A good mentor is a goldmine, while a bad mentor can be anything but that. Mentorship is important though not a must! Conversely, one must be willing to learn, and this goes on both sides. In the end a mentor is someone with deeper understanding and experience, which are relative considering the tasks and problems ahead. Often one tries to solve with mentors problems of communication inside the teams, respectively the availability of resources for learning or job activities. It works in some areas, while in others better communication and escalation channels need to be found. A mentor should help one progress on the technical and non-technical aspects through supervision of the progress, feedback, advices, communication to management, etc.

Connecting with experienced professionals and mentors has provided me with diverse perspectives and guidance. Their feedback has been instrumental in navigating complex BI challenges and advancing my strategic thinking.

Analyser les données en Business Intelligence, c'est comme écouter une conversation entre les chiffres. Chaque indicateur de performance raconte une histoire sur vos projets, révélant à la fois vos succès et vos axes d'amélioration. Si l'engagement des utilisateurs sur vos tableaux de bord est faible, c'est un signal d'alarme pour ajuster la visualisation ou la pertinence des données. En prenant le temps d'écouter ces retours, vous ne faites pas que peaufiner vos compétences techniques; vous créez des solutions BI qui résonnent vraiment avec les besoins de votre équipe. En fin de compte, chaque donnée analysée est une occasion de grandir et d'innover.

Data can lie a lot when is the outcome of improperly defined processes, systemic quality issues, lack of knowledge, and folklore! Performance metrics can be defined when processes can be standardized, which can be done in theory, though there's lot of variation involved (e.g. by redefining the problem, requirements, views, deliverables, etc.). One can try to standardize BI processes and track performance, though from problem definition to final solution there are too many changes involved and issues that need to be addressed also in other areas. Many of the activities are not sequential but require multiple parallel attempts until the final outcome.

The problem with feedback is that it usually comes too late, when the technical resources are already involved in other activities. Thus, processing the feedback, clarifying the issues, changing the requirements, getting the necessary approvals can happen in time with major gaps in between. Unfortunately, the number of changes is often considerable, which hurts the performance of the people involved. In between there are many iterations that can involve redesign of the logic, retesting, and many other activities. Many issues need to be addressed in different areas: process management (incl. redesign), requirements management, data quality, data management, etc.

Sharing your knowledge and insights related to BI is a great way to enhance your skills in the BI field. When you share something, you will receive either positive or negative feedback. Based on this feedback, you can improve your skills in the BI field.

Sharing knowledge within the BI community isn't just a way to contribute—it's a means of gaining deeper insights and refining your own understanding. By teaching others, you reinforce your expertise and expose yourself to new questions that can challenge your assumptions. Engaging with peers through webinars, workshops, or even writing blog posts can position you as a thought leader while simultaneously inviting constructive feedback from a wider audience. This reciprocal exchange of knowledge cultivates a collaborative environment where both you and the community can thrive.

Self-reflection in BI extends beyond assessing past projects; it's about strategically planning for future development. Regularly evaluating your skills, decision-making processes, and how effectively you responded to feedback can reveal trends in your professional growth. This practice also provides the opportunity to identify gaps in your expertise and seek targeted learning opportunities. Reflection isn’t just a passive review—it’s an active process of questioning how you can evolve as a BI professional. It’s a habit that drives continuous improvement and long-term career success.