Integrating SparkLin with Microsoft Purview allows for capturing and visualizing end-to-end data lineage in Spark environments. This enhances governance, transparency, and audit readiness. The refined SparkLin codebase ensures seamless integration into data governance frameworks.
Managing SAP data is complex, especially with siloed teams and fragmented information. Without strong data governance, collaboration weakens, documentation suffers, and visibility declines.
For many organizations, establishing a modern data platform can be daunting. Microsoft Fabric proves however that it doesn’t have to be. Fabric is designed to simplify, unify, and empower your modern data platform. With easy setup, familiar integration and powerful features, the platform offers organizations of all sizes a unique opportunity to adopt data-driven strategies. Whether you’re just beginning to explore data analytics or are ready to elevate your data strategy, Fabric has something to offer.
In this blogpost, we share insights from our hands-on experience with Microsoft Fabric, including some intriguing benefits and lessons learned. Our goal? To inspire you and dispel any doubts, so that you feel confident that setting up a modern data platform using Microsoft Fabric is achievable in your organization too.
If your team has adopted Power BI in recent years, you've likely experienced its many advantages. However, the user-friendly nature of the tool can be a double-edged sword. In this article, we explore three common pitfalls we have seen organizations face when using Power BI. By addressing these pitfalls, organizations can maximize Power BI's potential to transform their data into meaningful insights and drive informed decision-making.
At Datashift, we've witnessed firsthand how Collibra can transform Data Governance practices and keeps pace with evolving market demands.
As a Data Architect at Datashift, I've had the opportunity to work extensively with Microsoft Fabric since its introduction. Over the past year and a half, Fabric has shown tremendous promise, but like any new technology, it has had its challenges.
Self-service BI allows business users to independently access, visualize, and analyse data. Although this sounds very promising for organizations, it also introduces challenges and potential pitfalls.
Many organizations still rely on tools like Excel and SharePoint to manage their data governance needs. However, the complexities and volume of modern data requires a more robust, scalable and efficient solution.
Enter modern data governance tools.
An AI that is trained on your specific data cannot be copied by competitors and is a very strong way to set you apart. Let's have a look at how you can fine-tune your AI systems on your specific data.
