Big Data
LLMOps blueprint for closed-source large language models
Semantic layer: Design principles and cloud-agnostic architecture
How to enhance MLOps with ML observability features: A guide for AWS users
Modern serverless data ingestion solution on AWS
Data democratization, the Goldilocks choice and culture change
Enterprise-grade ML platform in AWS: A starter kit
Data quality control framework for enterprise data lakes
Establishing advanced BI capabilities with Google Looker: A step by step tutorial
Deploy Data Platform on AWS in One Day
Turn data into insights faster with Grid Dynamics analytics platform starter kit on AWS cloud
5 steps to implementing a successful DataOps practice
From data lake to analytical data platform
How to use GCP and AWS big data and AI cloud services from Jupyter notebook
Add anomaly detection to your data with Grid Dynamics starter kit
Which enterprise data warehouse performs better for your workloads?
Why you need data quality automation to make data-driven decisions with confidence
How to create a serverless real-time analytics platform: A case study
Delivering actionable insights in real-time by moving from batch to stream processing: A digital media case study
Top business drivers of real-time analytics and machine learning in retail
How to achieve in-stream data deduplication for real-time bidding: A case study
Deploying and running an in-stream process service as a “Developer sandbox”
From reference architecture to reference implementation: Detailing the DevOps aspects of in-stream processing service
In-stream processing service blueprint
Overview of in-stream processing solutions on the market
How in-stream processing works
What is in-stream processing?
