In “ Designing a metadata-driven ETL framework with Azure ADF: An architectural perspective,” I laid the groundwork for a scalable, metadata-driven ETL framework using Azure Data Factory (ADF).

The need for effective Extract, Transform, Load (ETL) technologies that can manage the growing volumes of both structured and unstructured data in information lakehouse architectures is increasing due ...

Batch data processing is too slow for real-time AI: How open-source Apache Airflow 3.0 solves the challenge with event-driven data orchestration ...

Conversational data agents in Microsoft’s big data platform bring enterprise data and insights into AI-powered business processes.

Litmus has entered a strategic partnership with Microsoft to help deliver seamless edge-to-cloud industrial AI solutions. Litmus Edge, the firm’s industrial data operations platform, will be ...

Enter data orchestration, a strategy referring to the process of ingesting, transforming, translating, storing and synchronizing data across disparate sources and systems, all done behind the scenes.

Data orchestration will become ever more important, not just in collecting data, but in helping companies channel it effectively to inform decisions and drive business success.

The same can be said for orchestration. Data that enables orchestration must be accessible, trustworthy and digestible and that is not the natural state of supply chain data.

The open source Apache Airflow data orchestration technology is adding new features to help enterprises build better data pipelines and understand where data is coming from.