Flipboard

MAY 30, 2025

For the preceding techniques, the foundation should provide scalable infrastructure for data storage and training, a mechanism to orchestrate tuning and training pipelines, a model registry to centrally register and govern the model, and infrastructure to host the model. She has presented her work at various learning conferences.

AWS 130

AWS AI AI Database 130

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

IBM Journey to AI blog

AUGUST 1, 2023

models are trained on IBM’s curated, enterprise-focused data lake. Fortunately, data stores serve as secure data repositories and enable foundation models to scale in both terms of their size and their training data. Foundation models focused on enterprise value IBM’s watsonx.ai All watsonx.ai

AI 70

AI AI Machine Learning Machine Learning 70

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.

AWS 92

AWS Machine Learning Machine Learning AI 92

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.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

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. Data center career paths (techtarget.com) 10.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

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.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

IBM Journey to AI blog

JULY 27, 2023

Powering a knowledge management system with a data lakehouse Organizations need a data lakehouse to target data challenges that come with deploying an AI-powered knowledge management system. It provides the combination of data lake flexibility and data warehouse performance to help to scale AI.

AI 69

AI AI Data Scientist Data Quality 69

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

Flipboard

DECEMBER 6, 2023

The dataset Our structured dataset can reside in a SQL database, data lake, or data warehouse as long as we have support for SQL. In our use case, we use SQLDatabaseChain in the SQL generation, simplifying and orchestrating interactions between the database and the LLM.

SQL 166

SQL Database AWS Machine Learning 166

Alation

FEBRUARY 13, 2020

In his book titled “The Fourth Industrial Revolution,” Klaus Schwab describes the age as, “characterized by a much more ubiquitous and mobile internet, by smaller and more powerful sensors that have become cheaper, and by artificial intelligence and machine learning.”

Machine Learning 52

Machine Learning Machine Learning Big Data Big Data 52

phData

SEPTEMBER 27, 2024

Activity Schema Modeling: Capturing the Customer Journey in Action Now that we’ve got our Lego blocks of customer data, let’s talk about another game-changing approach that’s shaking up the world of customer data modeling: Activity Schema Modeling. These changes are streamed into Iceberg tables in your data lake.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

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.

Data Lakes 52

Data Lakes Predictive Analytics AI AI 52