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