Avoid common data modeling mistakes for data integrity. Skip to content ... etc.) have become a critical component of enterprise data architecture, ... Inconsistent or nonexistent naming patterns.

Case in point is this post from Kjell-Sverre Jerijærvi who points out the need and the notion of a common or Canonical "Data" Model. "An important topic when designin Topics ...

In this webinar Makesh Renganathan, Principal Product Manager at Informatica, will cover common architectural patterns in data integration and share his views on how to pick the best one for your ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

KEY TAKEAWAYS • Different types of AI models power rigorous applications, each tailored to specific tasks. Common types of AI models include machine learning, deep learning, natural language ...

There are at least three distinct styles or patterns for event-driven architecture, each at different levels of abstraction layers, which can be broadly categorized as: 1. Event Sourcing: This ...

There’s one common element in each of these fundamental business model changes—enterprise architecture. Each company drastically had to shift its strategic goals, business model, data ...