Many teams still work with fragmented pipelines, where knowledge is scattered across individuals. The logic is embedded in legacy tools within siloed teams. Enter dbt: a free (dbt core), open-source tool that empowers data teams to manage all their transformation logic directly in the datawarehouse using just SQL.
Your data isn’t lacking infrastructure. It’s lacking impact.
Product thinking brings the focus back to business outcomes—by treating data like a product, not a project.
This blog explores Datashift’s key strategies for a seamless migration. We’ll cover pre-migration planning, execution with piloting and iteration, and post-migration optimization to maximize Power BI’s benefits.
In 2025, AI-driven data quality, predictive analytics, and seamless tool integration will redefine business decision-making. Discover the top trends shaping data quality management.
Blood platelets present a unique healthcare supply chain challenge with their critical importance and extremely short shelf life. By precisely forecasting platelet demand, healthcare providers can better balance patient needs with resource optimization, resulting in reduced waste, significant cost savings, and more reliable care. This case study explores how advanced analytics transforms healthcare logistics while maximizing the impact of every blood donation.
AI applications have taken off across industries. From chatbots generating creative content to AI-driven automation in finance and customer service, businesses are seeing real impact. But as AI adoption grows, so do the challenges—bias in decision-making, transparency concerns, and even security risks like deepfake fraud. How can organizations ensure AI delivers value while staying responsible?
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.
Data lineage is more than a technical feature; it is a cornerstone for understanding how data flows, transforms and integrates across systems.
