A practical guide to Bronze, Silver and Gold, with a working Python and DuckDB example The post The Medallion Data Architecture: An Introduction appeared first on Towards Data Science .
Beyond basic graph retrieval: six production-oriented architectures for combining semantic search, knowledge graphs, and LLM reasoning. The post GraphRAG: A Practitioner's Guide to 6 Advanced Architec...
If you have ever wanted to actually build an LLM inference runtime yourself — pack your own weights, own every barrier, capture your own CUDA graphs — this is what that journey looks like on an H100. A step-by-step tour of a small runtime called annotated-llm-runtime, and the three bugs that produced most of the annotations.
A practical next step into partitions, shuffles, joins, caching, and execution plans. The post PySpark for Beginners: Building Intermediate-Level Skills appeared first on Towards Data Science .
What data teams need to build with AI to make self-healing data architecture a practical reality The post 7 Crucial Barriers Between Data Teams and Self-Healing Data Architecture appeared first on Towards Data Science .
The strategies, questions, and process I used to ace coding interviews. The post How I Mastered Data Structures and Algorithms for ML (In 6 Weeks) appeared first on Towards Data Science .
arXiv:2607. 11353v1 Announce Type: cross Abstract: The creation of digital collections involves not only the digitisation of content, but also the creation of catalogue records for it.
Starting with a local Parquet file, then joining it to data stored in the cloud The post Building a Data Lakehouse with DuckDB and DuckLake appeared first on Towards Data Science.
OpenAI and Datadog brand graphic with the OpenAI wordmark on the left, the Datadog logo on the right, and a central abstract brown fur-like texture panel on a white background.
Large language models (LLMs) are often asked to produce JSON conforming to a fixed schema, powering information extraction, tool calling, agentic planning, and knowledge-graph construction. Measuring how closely an output matches a gold reference is essential yet surprisingly hard: exact match is brittle, text similarity ignores structure, and an LLM judge is expensive, opaque, and non-deterministic.
Applying blockchain primitives to dataset versioning, provenance, and integrity assurance The post Ensuring Data Integrity with Cryptographic Hashing and the Ethereum Blockchain appeared first on Towards Data Science .
The article argues that for small‑to‑medium enterprises, the most disruptive yet essential step toward data maturity is to rebuild or strengthen a solid knowledge foundation layer. It stresses that this initiative must be evidence‑backed and minimally disruptive to current processes, and it proposes a low‑impact data strategy that adapts to evolving data flows. The authors emphasize that knowledge graph techniques will become indispensable in AI‑powered enterprises if designed modularly, dynamically, and cross‑functionally.