ML technologies offers a host of benefits: higher productivity, lower customer churn, actionable data, and more. Here are some stages where the machine learning can be applied in ServiceNow platform.
Suggested Reading
Understanding the Search Layer in MongoDB: Observability and Diagnostics in Practice
A practical exploration of MongoDB Search, focusing on how the search layer operates, why observability matters, and how to approach diagnostics in modern architectures.
Anthropic’s New AI Can Write 60-Year-Old COBOL Code
AI can now generate and interpret legacy COBOL, but the real impact is not code replacement. The shift is economic and architectural. This analysis explains where AI truly accelerates modernization and where the hard risks still live
MongoDB Data Modeling: The Truth About Relationships, Data Duplication, and Performance
MongoDB Data Modeling: The Shift to an Application-First Mindset Most data models don’t break in…
Scaling MongoDB to 100K+ Writes per Second
Sustaining 100K+ writes per second in MongoDB is not a tuning trick — it is an architectural decision. This article breaks down how to design a sharded cluster using realistic Atlas hardware (32GB RAM, 8 CPU, standard storage) and achieve linear horizontal scaling through deterministic shard key distribution, clean write paths, and disciplined index strategy.
Gödel, Escher, Bach: learning to think by walking in circles
Some books are not meant to be read linearly. They pull you into a recursive journey where music, art, and mathematics begin to speak the same language. Gödel, Escher, Bach is one of those rare works that teaches you not what to think, but how thinking itself folds back on itself.
Data Quality by Design
Data quality is not a downstream fix.
It is a structural property of the system.
Only when data management decisions converge into a Golden Record does quality become measurable, explainable, and governable over time.
