Tackling Data Challenges with Power Platform

As a Power Platform professional, I’ve learned that the quality of your data is non-negotiable. The deeper your solution integrates with core data systems, the more critical it becomes to ensure your data is accurate, accessible, and scalable.

Over the years, I’ve encountered several recurring data challenges, each with its own lessons and strategies. Here’s a closer look at what I’ve faced and how I’ve tackled it.

Power Platform Data Challenge #1

Wrestling with Legacy Systems

Legacy systems are like the grumpy old-timers of the tech world, unpredictable and often difficult to work with. In my experience, the most effective way to integrate these systems is to prioritize APIs first and fall back on Robotic Process Automation (RPA) when APIs aren’t an option.

APIs are generally more reliable and easier to maintain, but they are not without their downsides. Costs and security concerns can arise depending on how the data transfer is managed. RPA, while useful, is usually my last resort because it is less efficient and harder to scale.

Power Platform Data Challenge #2

Breaking Down Data Silos

Data silos are one of my biggest frustrations. If I can’t access the data, neither can the solutions I’m building. Breaking down these barriers often involves ensuring data availability across multiple systems, which is easier said than done.

Security concerns can arise, especially if you are dealing with public cloud services. My go-to solution is Microsoft Dataverse. It acts as a centralized hub or single source of truth that everything can connect to and communicate through. For larger, more intensive solutions, I recommend investing in unified data platforms designed to handle enterprise-level demands.

Power Platform Data Challenge #3

Ensuring Data Quality

“Garbage in, garbage out” is a harsh but accurate mantra when it comes to data. Inconsistencies, missing information, and inaccuracies can derail even the best solutions. Unfortunately, no technology can magically clean your data, so this responsibility lies squarely with the data owners.

From my perspective, tackling this problem requires a two-pronged approach. First, you need a solid governance framework to manage data quality at an organizational level. Then, implement it technically using tools like Microsoft’s Power Platform Center of Excellence and Power Platform Framework, both of which provide excellent starting points.

Power Platform Data Challenge #4

Addressing Scalability

Scaling solutions is another challenge that comes up frequently. Whether you are moving from a low-performance database to something more robust or trying to handle sudden spikes in demand, scalability requires thoughtful planning.

This is where cloud-based solutions shine. Their ability to offer on-demand performance upgrades has saved me countless headaches. Every migration has its unique challenges, so flexibility and adaptability are key.

Power Platform Data Challenge #5

Managing Change Effectively

Even the most perfectly implemented solutions are useless if they are not adopted. Change management is often the unsung hero of a successful project. A solid knowledge transfer process is essential, covering both the technical and human aspects of the solution.

For me, this means taking the time to train stakeholders and ensuring they have access to clear, actionable documentation. Empowering users to own and adapt to the new systems is what makes changes stick.

The Power Platform is an incredible toolset, but like any technology, it requires thoughtful implementation and a strategic approach to data challenges. By addressing issues like legacy systems, data silos, and quality control, while planning for scalability and change management, you can unlock the full potential of the platform.

Every challenge is an opportunity to learn, and I’ve learned plenty. Here’s to building smarter, more effective solutions one data challenge at a time!