What are the most innovative approaches to solving BI problems in a mid-career role?

Nowadays: due to the volume of data generated and its availability, more and more companies are migrating from On-premise architectures to Cloud-based architectures. In fact, 100% of BI tools today offer cloud solutions under a SaaS model, with PowerBI standing out with Azure and also, Tableau that can connect to any cloud platform such as AWS or GCP. However, generative AI has opened a new research front where you can use it from AI integrations with SQL clients (using API integrations) or even ask the AI to generate exploratory charts for you. On this last point, Microsoft Fabric is undoubtedly a reference that is worth learning and exploring, to understand what is next in the BI industry.

I am agree with that in order that the BI process need to be complemented with an Agile process that permit you obtain feedback in any step of the chain

Some good ideas to materialize the agile approach and design thinking are to use tools that allow the integration of clients, team members and other stakeholders. Although there are many tools (paid and free), I would recommend as a test, starting with Trello to start with a Kanban board (foundations of any agile process - basis of SCRUM framework) and complement it with Hotjar, Mural or Miró as a canvas for mockups, brainstorming and other collaborative processes. If after 2 months of testing, you see that Trello and the other tools work well for your BI dynamics, start looking for more robust tools and perhaps guidance from Agile implementers to get the most out of this way of work.

Embrace data storytelling techniques to communicate insights effectively. Convert raw data into compelling narratives that resonate with stakeholders, making it easier for them to understand and act upon the information.

Integrate self-service BI platforms that empower business users to create their own reports and dashboards. This reduces the dependency on IT for routine reporting tasks.

If you are going to invest your time in learning new trends or tools, first validate which ones really are or will be demanded by the market. A good reference: Garner's Magic Quadrant. As soon as you identify the leading tools, review their latest releases or 2024's roadmap to understand what you need to learn and investigate.

Select a colleague who has more experience (time or practice) in the field in which you would like to improve, find a 45-minute in-person space and ask them to: Ask for his/her opinion of your performance based on real facts, ideally on behaviors that he/she has perceived. Ask him/her to emphasize the opportunities for improvement that he would advise you to polish, establishing a goal or objective in a specific time frame. And finally, look to have a new session with the same colleague, so that he has a specific frequency to give and receive feedback and validate your progress.

Answering the question: What are the most innovative approaches to solving BI problems in a mid-career role? I would say that a better understanding of how pipelines work, a bit of Python and processing tools like Apache Spark or Google Dataflow - although this is more the domain of a Data Engineer - are key skills to understand how to enrich data, improve the models (in granularity and groupability) and thus be able to improve the visualization layer to generate even more value for the business.