Remove 2020 Remove Data Lakes Remove Data Modeling
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Schema Evolution in Data Lakes

KDnuggets

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.

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Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker

AWS Machine Learning Blog

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access. This framework considers multiple personas and services to govern the ML lifecycle at scale.

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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. However, these tools have functional gaps for more advanced data workflows.

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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning Blog

data # Assing local directory path to a python variable local_data_path = ". . By using the flexible document data model of MongoDB Atlas, organizations can represent and query complex knowledge entities and their relationships within Amazon Bedrock. Data Architect, Data Lake at AWS. Satish Sarapuri is a Sr.

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