I think data exists to tell stories and I love to be the one to tell them.

BI is the kitchen and data the raw ingredient

Business Intelligence (BI) is the key to transforming raw data into actionable insights that drive profitability and efficiency. In today's data-driven world, businesses that harness the power of BI can uncover hidden patterns, optimize operations, and make data-backed decisions with confidence, the key is related to who handles your data and their expertise.

Me as a BI professional

As a Business Intelligence (BI) professional with several years of experience in the data industry, I specialize in transforming complex datasets into actionable insights that drive strategic decision-making. My expertise spans data analysis, visualization, and automation, allowing businesses to not only understand their data but also leverage it for tangible growth. What sets me apart is my ability to bridge the gap between technical solutions and business needs—translating raw data into clear, impactful narratives that empower organizations to make informed decisions. Additionally, my proficiency in Flutter enables me to develop custom data-driven applications, providing businesses with tailored BI solutions beyond traditional dashboards. Whether optimizing workflows, implementing predictive analytics, or designing scalable data architectures, my focus is always on maximizing the value of data to create measurable business impact.

Some tools and platforms I use for my work and projects

My process working with projects focuses on the following steps

Develop an overview of the desired outcome while understanding the key points of the requirement.

Requirement gathering

Data sourcing

Planning and stratification

Data transformation

Visualization and prototyping

Showing and receiving feedback

Refininement

Delivering and standarizing

Create action plans according to established objectives, define delivery timelines, and anticipate immediate and future difficulties in order to achieve goals.

Compiling all the data sources needed for the project and define its replicability model and standardization level, as well as determine the frequency of its acquisition, taking into account its design.

Usually the data sources are not tailor-made and in this process the information is adapted according to the final deliverables, all this through data transformation processes that require some changes, whether these be data types, text manipulation or even the creation of special fields or those that operate at a high level.

At this point, the data provides implicit information with a user perspective, but requires the creation of a complete, summarized, and simple approach so that both technical and non-technical users can understand the views and business situations they intend to show. This process usually requires refinement and input from stakeholders, which is why it can be viewed in terms of prototypes or MVPs.

Today's business understands the need to have valuable products on the market as quickly as possible and improve according to user feedback. Of course, the product must have the necessary quality standards for its launch. Here, these products are shown to stakeholders to proceed with refinement and socialize possible improvements and value to the business.

In this step, special focus is placed on the details of the deliverables and all the added value and previous feedback points are worked on.

Finally, the requested work is delivered, but with a vision for the future, making the work carried out sustainable, reusable, and even, if possible, standardizing updates automatically.

Your ally in data intelligence

I am a business intelligence professional, creating effective solutions with SQL, Power BI, and Python to optimize your processes and visualize your data clearly and accurately.

Data analysis expert

My mission is to transform data into decisions

The goal is to create data pipelines and dashboards of key indicators, helping to make informed and strategic decisions based on reliable and optimized data.