How can you use your data modeling portfolio to differentiate yourself from other BI professionals?

Building a strong data modeling portfolio can help differentiate yourself as a BI (Business Intelligence) professional in a competitive job market. Here are some strategies to showcase your skills and stand out from other candidates: Diverse Project Showcase: Problem-Solving Narratives: Data Visualization Samples: Data Quality Assurance: Performance Optimization: Incorporate Industry-Specific Projects: Version Control and Documentation: Collaboration and Teamwork: Professional Growth and Certifications: GitHub or Online Repository: Quantifiable Results: Soft Skills and Leadership:

There could be a real portfolio from the experience to showcase and some creative open source projects/challenges solutions. Both are great to have. - The first, real life experience, you need to choose the best and most interesting from those that are allowed to disclose. - The second, feel free to search for those challenges that inspire you: from DataCamp, Maven Analytics, GitHub, etc. The beauty is that you can create a data story using any BI tool. You are not limited. And of course you can just use a demo dataset, for example, from Microsoft - AdventureWorks, some other one or create your own. Also, for your portfolio, you can use the solutions that you created for the technical interviews that you had. Have fun!

Certainly! When selecting projects for your data modeling portfolio, consider showcasing a diverse range of skills by including projects with varying complexities. This not only demonstrates your versatility but also provides a holistic view of your capabilities. Additionally, emphasize the real-world impact of your projects by highlighting how your data modeling efforts contributed to solving specific business challenges or improving processes. This approach can give potential employers or collaborators a clearer understanding of the value you bring to the table.

As you document your process, consider calling out the obstacles you encountered and overcame. This detail showcases not just your technical skills, but also your problem-solving abilities, resilience, and creativity. By emphasizing your ability to succeed despite challenges, you provide a narrative of growth and adaptability.

Documentation is needed everywhere. And while you work on a project, or afterwards, create key notes. If you have some project mentioned in the portfolio, be prepared to answer the questions about it. You’ll definitely get something like: - What did you try to achieve?/Your goals? Did you achieve them? What are the key findings? - What is the impact that you brought? - What did you try? What worked? What failed? Why did you choose this approach to solve this? What would you do differently if you start over? - Which obstacles did you overcome?/Any bottlenecks? Do you know how to avoid them the next time? - What are the things that you are proud of? So better prepare the answers while you fully remember the details of the project.

As you document your data modeling projects, consider weaving a narrative that not only outlines the technical aspects but also emphasizes the strategic decisions you made. Highlight the decision-making process behind choosing specific modeling techniques, tools, and methodologies. This storytelling approach provides a more engaging perspective, offering readers insight into your problem-solving mindset and the thoughtful considerations that shaped your data modeling decisions. This not only makes your portfolio more compelling but also helps potential collaborators connect with the reasoning and creativity behind your data modeling journey.

While showcasing your data modeling portfolio, it’s important to clarify which approach did you use and why, how did you optimize the performance, eliminated redundancies, etc. Mention that you created a good documentation for the data model, so that it can be well maintained. That there is a model created in draw.io for example. And most importantly, what was the business feasible impact. Something measurable. People spend less time, how much, department saved money, how many…

It pays to underscore the practical impact of your projects. Illustrate how your work advances business objectives, such as enhancing customer understanding or streamlining operations. Demonstrate tangible outcomes, like increased efficiency or revenue growth, with relevant metrics and case studies. Your portfolio becomes more compelling by highlighting these real-world applications, bridging the gap between complex data work and strategic business value.

In showcasing your value as a data modeler, go beyond technical details and emphasize the tangible results that emerged from your efforts. Quantify the impact by highlighting measurable improvements in data quality, system performance, or other key metrics. Integrate feedback and testimonials to provide a human touch, demonstrating not only the success of your data models but also the positive experiences and collaborations with project stakeholders. This holistic perspective not only communicates your technical prowess but also underscores your ability to bridge the gap between data modeling and real-world business outcomes, making your portfolio more impactful and relatable.

Regularly updating and optimizing your data modeling portfolio not only reflects your commitment to staying current but also showcases an evolving skill set. Treat your portfolio as a dynamic narrative of your growth, incorporating new projects to demonstrate continuous learning and adaptation to industry trends. Additionally, use feedback as a compass for improvement, refining your portfolio based on insights gained from each project's outcomes. When it comes to presentation, ensure clarity and accessibility by organizing information logically and maintaining a consistent style.

View your data modeling portfolio not just as a collection of projects but as a powerful tool for personal branding. Leverage it strategically by integrating the portfolio link into your professional documents, transforming it into a visual representation of your expertise. During interviews or interactions, use specific examples from your portfolio to articulate your skills and problem-solving abilities effectively. Additionally, proactively engage with the data modeling community, sharing your portfolio to solicit feedback and insights.

To create a data modelling portfolio, you can: - Choose relevant and interesting projects that show your problem-solving skills. - Use a variety of tools and techniques to demonstrate your proficiency and knowledge in data modelling. - Tell a compelling story that explains the context, purpose, process, results,and insights of your projects. - Provide evidence and feedback to prove your skills and achievements. - Keep it updated and organized to show your growth and development. When you raise your rates, communicate clearly and respectfully with your clients, explain the reasons, highlight the benefits, and offer options. Be prepared for some pushback or negotiation, and be willing to compromise or walk away if necessary.

N?o basta fazer uma análise bem fundamentada se os insights trazidos por ela n?o forem de fácil leitura. Nessa hora o design vai fazer a diferen?a: tenha painéis intuitivos, com tipografia, cores e formas agradáveis aos usuários. Uma dica é come?ar com um template, mas evoluir pensando sempre nos cenários de uso mais relevantes para quem for consumir a informa??o.

Articulate the use case, the practical application and results….. a feedback loop. No point in monitoring a quick ratio unless it’s possible to interpret, apply an action and have a result (positive or negative)