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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

Flipboard

This post is part of an ongoing series about governing the machine learning (ML) lifecycle at scale. This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The data mesh is a modern approach to data management that decentralizes data ownership and treats data as a product.

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8 Data Lake Vendors to Make Your Data Life Easier in 2023

ODSC - Open Data Science

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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How to Build ETL Data Pipeline in ML

The MLOps Blog

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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Why Easier Governance Is Superior Governance

Alation

Sheer volume of data makes automation with Artificial Intelligence & Machine Learning (AI & ML) an imperative. Menninger outlines how modern data governance practices may deploy a basic repository of data; this can help with some level of automation. Data lakes are repositories where much of this data winds up.

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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric and data mesh as concepts have overlaps.

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Modern Data Management Essentials: Exploring Data Fabric

Precisely

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

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Snowflake for Commercial Banks, Everything You Need to Know

phData

By leveraging cloud-based data platforms such as Snowflake Data Cloud , these commercial banks can aggregate and curate their data to understand individual customer preferences and offer relevant and personalized products.

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