Fragmented stacks, hand-coded ETL and static dashboards are dead; AI is forcing data management to finally grow up in 2026.

Mason Clutter In an era of rapidly evolving privacy legislation and growing public demand for data protection, organizations face increasing pressure to stay compliant while remaining operationally ...

For many organizations, the widespread use of decentralized tools, apps, and cloud provider platforms by individual teams is both a blessing and a curse. On the one hand, it gives employees maximum ...

The convergence of structured and unstructured intelligence presents challenges for enterprise generative AI (GenAI) architecture. To address this, data platforms must unify data pipelines, metadata, ...

Deepak Yadav is an Engineering Leader at Amazon, Data & ML expert, ex-Ask.com, formerly with Amdocs, and Data Influencer. Generative AI is emerging as a transformative force in data engineering, ...

As AI moves from hype to measurable results, one truth is becoming clear: Enterprise AI needs business context to be fully ...

Higher education has a data problem. It’s not new: Institutions have been grappling with fragmented data for a long time. Especially when it comes to student information, sprawl is the norm. Data is ...