Building Reliable EMR Pipelines With Custom AMIs and Step Functions
The goal is not custom AMIs for every workload. It is to make dependency management, patching and recovery explicit platform responsibilities rather than repeated job-level tasks.
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The goal is not custom AMIs for every workload. It is to make dependency management, patching and recovery explicit platform responsibilities rather than repeated job-level tasks.
This project creates a daily digest for sellers in an enterprise system. Each seller handles accounts at a set of companies and needs to know when something happens at one of them:...
EMR and EHR releases impact clinical workflows, patient data, integrations, security and compliance. This blog describes how healthcare enterprises can transition from regression t...
Originally appeared on OmbuLabs Blog.A few months ago, we were tasked with building a platform that aggregates events across an entire city, concerts, gallery openings, museum exhi...
the strange space in between
Asynchronous processing pipelines are a cornerstone of modern distributed systems, but wiring them together reliably can be complex. A typical pipeline built with queues or message...
Most enterprise data problems are not caused by machine learning models or dashboard tools. They usually start much earlier in the pipeline. A reporting table misses records after...
Session 2 of The Production RAG HandbookContinue reading on Medium »
With AWS Glue 6.0, you can build real-time, near-real-time, and batch data pipelines on a single platform. Using a financial market-risk example, learn how to flag high-risk trades...
The following is a guest article by Diana Lam, Marketing Specialist at MIMIC A patient walks into a physician’s office with persistent neurological symptoms—headaches and dizziness...
One of the first features users expect from an AI application is deceptively simple: Upload a document. Ask questions. Get accurate answers. Whether you're building an internal...
For the past two decades, most enterprise data engineering systems have been built on one default assumption: People understand the system. The system executes the pipeline. Engine...
In this post, we show how Apache Celeborn resolves this trade-off for Amazon EMR on EKS and Amazon EMR on EC2, improving job reliability while unlocking additional cost savings.
How we split a tightly coupled Python pipeline into independently deployable services The post When One Process Becomes Too Much: Splitting a Pipeline into MCP Services appeared fi...
Large Language Models (LLMs) have fundamentally transformed modern software development by enabling engineers to build intelligent applications that can reason, plan, invoke extern...
Analytics teams do not get too upset about small errors. If a product dashboard is off by half a percent on a Tuesday, nobody files a ticket. If your marketing funnel counts some w...
AWS Glue makes it easy to get a PySpark pipeline running quickly. It is significantly harder to build one that stays maintainable as logic grows, performs reliably at scale, and do...
В исходном orders.csv было 11 строк. До BI-витрины дошло 7, а валовая сумма 4720.30 после применения бизнес-правил превратилась в 2200.30 выручки. Четыре строки не исчезли: каждая...
In the world of digital health, the "Cloud-First" approach is hitting a massive wall: Privacy. Sending raw, sensitive Bio-signal data like Electrocardiograms (ECG) to a central ser...
Background: Following 2 decades of electronic medical record (EMR) adoption, most large public health systems hold comprehensive digital clinical data but lack the complementary in...
If you ask an AI coding agent to write a standalone Python script to parse a single JSON file, it will likely give you a perfect answer in seconds. But the same agent often breaks...
Several of the e-commerce stores we build and run ship with MRW, one of the main carriers in Spain and Portugal. Until recently, shipping an order meant leaving the store: open MRW...
One of Canada’s largest railway networks spans roughly 20,000 route miles across...
About a year ago, I was building a terminal-based workflow manager called Glyph.Flow. It was mostly a learning project. I wanted to understand Python better, experiment with Textu...
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