AWS Machine Learning Blog

APRIL 18, 2023

With the recently launched Amazon Monitron Kinesis data export v2 feature , your OT team can stream incoming measurement data and inference results from Amazon Monitron via Amazon Kinesis to AWS Simple Storage Service (Amazon S3) to build an Internet of Things (IoT) data lake. Choose Next.

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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 key is to choose a solution that can effectively host your database and compute infrastructure.

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AWS Machine Learning Blog

APRIL 30, 2025

ENGIEs One Data team partnered with AWS Professional Services to develop an AI-powered chatbot that enables natural language conversation search within ENGIEs Common Data Hub data lake, over 3 petabytes of data. Amer Elhabbash is a Senior Data & AI Delivery Consultant with AWS Professional Services.

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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?

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AWS Machine Learning Blog

NOVEMBER 22, 2023

You marked your calendars, you booked your hotel, and you even purchased the airfare. Embeddings can be stored in a database and are used to enable streamlined and more accurate searches. You can use an embeddings model in Amazon Bedrock to create vectors of your organization’s data, which can then be used to enable semantic search.

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ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling.

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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.

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IBM Journey to AI blog

DECEMBER 16, 2022

You have a specific book in mind, but you have no idea where to find it. You enter the title of the book into the computer and the library’s digital inventory system tells you the exact section and aisle where the book is located. It uses metadata and data management tools to organize all data assets within your organization.

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phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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ODSC - Open Data Science

JULY 11, 2023

What are the similarities and differences between data centers, data lake houses, and data lakes? Data centers, data lake houses, and data lakes are all related to data storage and management, but they have some key differences. Not a cloud computer?

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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.

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IBM Journey to AI blog

JULY 1, 2024

If you say “manual stitching” among data professionals, everyone cringes and runs. In her book, Data lineage from a business perspective , Dr. Irina Steenbeek introduces the concept of descriptive lineage as “a method to record metadata-based data lineage manually in a repository.”

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phData

SEPTEMBER 27, 2024

. “ This sounds great in theory, but how does it work in practice with customer data or something like a ‘composable CDP’? Well, implementing transitional modeling does require a shift in how we think about and work with customer data. It often involves specialized databases designed to handle this kind of atomic, temporal data.

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ODSC - Open Data Science

NOVEMBER 22, 2023

Data Version Control for Data Lakes: Handling the Changes in Large Scale In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management.

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