Microsoft Fabric: Build a future-proof data platform in 7 steps
Implementing a data platform more and more organizations want to do it. Because with a data platform, you’re ready for the future. You can make better use of AI, gain more control over costs, and have greater insight into your performance. That level of flexibility makes your organization future-proof. That’s what you want!
But how exactly do you build a data platform that truly delivers results? It requires specific expertise that many organizations don’t have in-house. As a result, they often don’t know where to start. Or they take an intuitive first step, only to get stuck halfway through the process.
In this blog post, we’ll walk you through our proven approach — a seven-step plan to eliminate noise and guesswork!
1. Infrastructuur
A modern data platform stands or falls with its foundation. That’s why it’s essential to first set up the core components within Azure that will form the building blocks of your data platform. How will you store your organization’s data? How will you transform it? And how will you manage the related processes? The answers to these questions form the foundation of your infrastructure.
2. Network initialization and requirements
How will the different components communicate with each other? Are you dealing with sensitive data that requires higher security standards? To what extent is it acceptable for traffic to pass over the public internet? During this step, we gather the right input from all stakeholders. Based on that, we define the requirements to build a secure and scalable network structure.
3. Platform deployment
Time to set up the architecture! For this step as well, we gather the necessary requirements. Which data do you want to view in real time? And which data only needs to be retrieved once per hour, day, or week? It’s important to make these decisions early in the process. This allows us to build a solid architecture and gives you a clear overview of the overall cost structure.
4. Data Lake
To set up your Data Lake, we connect source systems and structure organizational data. We examine which sources you want to connect and how you want to do so. Together, we define what your data layers will look like and how we will transform and structure the data. At Wortell, we work with three layers: bronze (raw data), silver (cleansed and transformed data), and gold (structured and fully reliable data). In other words, the outcome of this process is a clean, trustworthy dataset.
5. Data models and reports
During this step, front-end developers start modeling the data. They connect data in such a way that they build in a safety margin and create a powerful, reusable data model. From this, you can generate reports for the business. This is done using data from the gold layer, as it serves as a single point of truth, one reliable source that everyone in the organization can work with.
6. Testing and validation
Because you want to ensure quality and reliability in every part of the process, it’s important to test everything thoroughly. During this step, we verify that the data is being retrieved correctly. We replicate the end-to-end process to check at each stage whether the new dashboard displays the same variables as the old one. We also confirm that the final output is accurate.
7. Handover to operations
Do you have a team of engineers who will be working with the data platform? At Wortell, we aim to make organizations self-sufficient. That’s why we involve your engineers throughout the project. We show them how we set up the architecture and connect data sources, so we can ensure a smooth handover in the final step.
If you prefer to outsource the management and further development, that’s possible too, in that case, we hand over the data platform to our internal operations team.
With this approach, we’ve already successfully implemented Microsoft Fabric for dozens of organizations.