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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.

SQL 52
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Unbundling the Graph in GraphRAG

O'Reilly Media

Store these chunks in a vector database, indexed by their embedding vectors. The various flavors of RAG borrow from recommender systems practices, such as the use of vector databases and embeddings. By the numbers: Run entity resolution to identify the entities which occur across multiple structured data sources.

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Data Intelligence empowers informed decisions

Pickl AI

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

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

AWS Machine Learning Blog

Their data pipeline (as shown in the following architecture diagram) consists of ingestion, storage, ETL (extract, transform, and load), and a data governance layer. Multi-source data is initially received and stored in an Amazon Simple Storage Service (Amazon S3) data lake.

AWS 109
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How to Build an Experiment Tracking Tool [Learnings From Engineers Behind Neptune]

The MLOps Blog

This layer is where you encode the rules of the experiment tracking domain and determine how data is created, stored, and modified. You can have other clients, like integrations with a model registry, data quality monitoring components, etc. Of course, a relational database would be valuable here.