AWS Machine Learning Blog

DECEMBER 29, 2022

The use of RStudio on SageMaker and Amazon Redshift can be helpful for efficiently performing analysis on large data sets in the cloud. However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling.

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phData

NOVEMBER 9, 2023

The primary objective of this idea is to democratize data and make it transparent by breaking down data silos that cause friction when solving business problems. What Components Make up the Snowflake Data Cloud?

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phData

SEPTEMBER 20, 2023

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

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Dataconomy

APRIL 27, 2023

This evolution led to the emergence of multimodal databases that can store and process not only relational data but also all other types of data in their native form, including XML, HTML, JSON, Apache Avro and Parquet, and documents, with minimal transformation required.

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phData

APRIL 2, 2024

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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Flipboard

DECEMBER 4, 2024

However, building data-driven applications can be challenging. It often requires multiple teams working together and integrating various data sources, tools, and services. For example, creating a targeted marketing app involves data engineers, data scientists, and business analysts using different systems and tools.

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