Remove Data Governance Remove Data Lakes Remove Data Science
article thumbnail

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. However, as data volumes and complexity continue to grow, effective data governance becomes a critical challenge.

article thumbnail

Data lakes vs. data warehouses: Decoding the data storage debate

Data Science Dojo

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

CI/CD for Data Pipelines: A Game-Changer with AnalyticsCreator

Data Science Blog

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. It offers full BI-Stack Automation, from source to data warehouse through to frontend.

article thumbnail

Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

article thumbnail

How to modernize data lakes with a data lakehouse architecture

IBM Journey to AI blog

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

article thumbnail

Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

Data governance challenges Maintaining consistent data governance across different systems is crucial but complex. Amazon AppFlow was used to facilitate the smooth and secure transfer of data from various sources into ODAP. The following diagram shows a basic layout of how the solution works.

AWS 86
article thumbnail

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.

ML 135