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Webinar takeaways: How to deal with common challenges in your data projects

27 November 2025
More on Data & Analytics

Main takeaways
  • Start with business strategy before defining your data strategy
  • Include People – Processes – Technology angels for long-term success
  • Look for an integrated, scalable analytics platform
  • Choose a technology stack that supports different analytics use cases (integration of different data sources, streaming data, descriptive analytics, advanced analytics,…)
  • Apply best practices like Medallion architecture and start with use cases that deliver the most business value
  • Create a strong data culture with governance, roles, processes, and continuous coaching
  • Maintain high data quality & governance with a unified platform, quality checks, and a data catalog

1. Start with a solid data strategy

Every successful data journey begins with a long-term vision on data, grounded in the business strategy. When organizations clearly understand where they want to go, they can define their current and future data needs and decide how people, processes, and technology will work together to support that vision. Based on the vision you will create clear data objectives, that are translated into a roadmap of projects. This ensures that data projects remain aligned with strategic goals rather than becoming isolated technical efforts.

2. Technology: Designing a platform that works

A strong data strategy must be supported by the right technology. The data platform should cover real business use cases, whether the organization operates on-premises, requires integration with operational systems, or depends on streaming and real-time data flows. Modern best practices such as the Medallion architecture help maintain clean, reliable data pipelines, while keeping business value at the center ensures that technology choices deliver measurable impact. We believe Microsoft Fabric is a modern and scalable analytics platform that can help to become more data driven.

3. People & Organization

Technology alone cannot create a data-driven organization. Success comes from building a culture that embraces analytics and uses data consistently for decision-making. This requires a clear governance framework and well-defined roles and responsibilities. Developing internal champions, offering continuous coaching, and celebrating successes all help embed data into everyday work and decision processes.

4. Data Quality & Governance

High-quality, trustworthy data is essential for evidence-based decisions. Finance teams, in particular, have a valuable opportunity to lead their organizations toward more data-driven operations. Maintaining strong data quality and governance means creating a unified platform, implementing systematic quality checks, and using a data catalog to centralize and clarify definitions and reports. Monitoring Power BI usage and access provides oversight, while a formal governance structure ensures that data remains managed, secure, and reliable as the organization grows.

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