KDnuggets

JANUARY 16, 2020

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.

Data Lakes 221

Data Lakes Data Warehouse Data Modeling Data Models 221

AWS Machine Learning Blog

OCTOBER 20, 2023

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.

ML 136

ML ML AWS Data Lakes 136

DagsHub

DECEMBER 11, 2023

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.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

Flipboard

MAY 30, 2025

For the preceding techniques, the foundation should provide scalable infrastructure for data storage and training, a mechanism to orchestrate tuning and training pipelines, a model registry to centrally register and govern the model, and infrastructure to host the model.

AWS 117

AWS AI AI Database 117

AWS Machine Learning Blog

OCTOBER 11, 2024

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.

Database 107

Database AWS Clustering Data Lakes 107