AWS Machine Learning Blog

JUNE 12, 2024

The main idea is to supply historic data to an ML algorithm that can identify patterns from the past and then use those patterns to estimate likely values about unseen periods in the future. Amazon has a long heritage of using time series forecasting, dating back to the early days of having to meet mail-order book demand.

ML 124

ML ML AWS Data Lakes 124

O'Reilly Media

OCTOBER 19, 2021

Adapted from the book Effective Data Science Infrastructure. Data is at the core of any ML project, so data infrastructure is a foundational concern. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

ML 145

ML ML Data Scientist AWS 145

ODSC - Open Data Science

JULY 27, 2023

Choosing a Data Lake Format: What to Actually Look For The differences between many data lake products today might not matter as much as you think. When choosing a data lake, here’s something else to consider. When choosing a data lake, here’s something else to consider.

Data Lakes 52

Data Lakes SQL AI AI 52

Flipboard

DECEMBER 6, 2023

These datasets are often a mix of numerical and text data, at times structured, unstructured, or semi-structured. needed to address some of these challenges in one of their many AI use cases built on AWS. The dataset Our structured dataset can reside in a SQL database, data lake, or data warehouse as long as we have support for SQL.

SQL 168

SQL Database AWS Machine Learning 168

phData

FEBRUARY 14, 2023

Tips When Considering Streamsets Data Collector: As a Snowflake partner, Streamsets includes very intricate documentation on using Data Collector with Snowflake, including this book you can read here. Data Collector can use Snowflake’s native Snowpipe in its pipelines.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Want to learn more?

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52

AWS Machine Learning Blog

APRIL 30, 2025

This post explores key insights and lessons learned from AWS customers in Europe, Middle East, and Africa (EMEA) who have successfully navigated this transition, providing a roadmap for others looking to follow suit. Il Sole 24 Ore leveraged its vast internal knowledge with a Retrieval Augmented Generation (RAG) solution powered by AWS.

AWS 66

AWS AI AI Machine Learning 66

AWS Machine Learning Blog

FEBRUARY 12, 2025

Many organizations store their data in structured formats within data warehouses and data lakes. Amazon Bedrock Knowledge Bases offers a feature that lets you connect your RAG workflow to structured data stores. The following is a sample architecture for a secure and scalable RAG-based web application.

AWS 89

AWS Machine Learning Machine Learning AI 89