For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of ...

Sydney Zoo is streamlining its data architecture, using Microsoft Fabric to consolidate multiple siloed databases into a ...

Why is the language developers and DBAs use to organize data such a mess? Here are 13 reasons we wish we could quit SQL, even ...

Cloudsmith, a leading cloud-native artifact management platform, is releasing its ML Model Registry, extending enterprise-grade governance and security to the machine learning models and datasets ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot ...

Enterprise data platforms increasingly unite analytics, governance and orchestration, with new generative and agentic AI-enabled features to improve autonomy and speed.

Data Modeling: Developing fact and dimension tables optimized for analytical queries. Analytics & Reporting: Creating SQL-based reports and dashboards for actionable insights.

For leaders looking to take on this kind of change, my advice is simple. Create space for collaboration, keep the accountability clear and build with empathy.

About Building a modern data warehouse using SQL Server, including ETL processes, data modeling and analytics.

Deep learning-based prediction models for High-Level Synthesis (HLS) of hardware designs often struggle to generalize. In this paper, we study how to close the generalizability gap of these models ...