Remove Data Pipeline Remove Data Quality Remove System Architecture
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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

It seems straightforward at first for batch data, but the engineering gets even more complicated when you need to go from batch data to incorporating real-time and streaming data sources, and from batch inference to real-time serving. Without the capabilities of Tecton , the architecture might look like the following diagram.

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What are the Biggest Challenges with Migrating to Snowflake?

phData

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture.

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Top Big Data Interview Questions for 2025

Pickl AI

Key challenges include data storage, processing speed, scalability, and security and compliance. What is the Role of Zookeeper in Big Data? Zookeeper coordinates distributed systems by managing configuration, synchronisation, and group services. How Do You Ensure Data Quality in a Big Data Project?

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Generative AI for agriculture: How Agmatix is improving agriculture with Amazon Bedrock

AWS Machine Learning Blog

Agmatix’s technology architecture is built on AWS. Their data pipeline (as shown in the following architecture diagram) consists of ingestion, storage, ETL (extract, transform, and load), and a data governance layer. AWS Glue accesses data from Amazon S3 to perform data quality checks and important transformations.

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