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.
Data lineage is more than a technical feature; it is a cornerstone for understanding how data flows, transforms and integrates across systems.
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.
While it used to be only available in Power BI, you can now build Default Semantic Models directly in Fabric using your tables from the Lakehouse or Warehouse.
Let’s dive into how we troubleshooted such performance issues and how Hyperscale came to the rescue.
A traditional data warehouse setup is no longer up to the many data challenges ahead. If you want to get ready for the future, regardless of the amount of data you are dealing with, you should check out Azure Synapse. This data analytics environment combines all components of a modern data platform.
Moving an on-premises data warehouse into the cloud can be daunting. Check out how we developed a tailor-made approach to navigate our client’s cloud migration challenges and deliver a cost-effective and future-proof Azure cloud environment.
The total cost of ownership of your Microsoft Azure environment can easily spin out of control if not managed well. Don't look any further, in this post we show you both passive and active ways to stay on top of your cloud costs at all times.
Choosing the right ETL tool for your company is a complex task. Both Azure Data Factory and on-premise tools have their strengths and weaknesses. It's important to understand the parameters and nuances involved to pick the right tool for the job. In this article we'll clarify the key differences and help you make the right decision for your business.
