Remove Artificial Intelligence Remove AWS Remove Data Lakes Remove Data Pipeline
article thumbnail

Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning Blog

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM). Their task is to construct and oversee efficient data pipelines.

AWS 100
article thumbnail

Mainframe Technology Trends for 2024

Precisely

With the emergence of cloud hyperscalers like AWS, Google, and Microsoft, the shift to the cloud has accelerated significantly. Instead of performing major surgery on their critical business systems, enterprises are opting for real-time data integration built around inherently reliable and scalable change data capture (CDC) technology.

AWS 52
professionals

Sign Up for our Newsletter

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

article thumbnail

Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

Flipboard

In this post, we will talk about how BMW Group, in collaboration with AWS Professional Services, built its Jupyter Managed (JuMa) service to address these challenges. For example, teams using these platforms missed an easy migration of their AI/ML prototypes to the industrialization of the solution running on AWS.

ML 95
article thumbnail

Identify cybersecurity anomalies in your Amazon Security Lake data using Amazon SageMaker

AWS Machine Learning Blog

Whether logs are coming from Amazon Web Services (AWS), other cloud providers, on-premises, or edge devices, customers need to centralize and standardize security data. After the security log data is stored in Amazon Security Lake, the question becomes how to analyze it. Subscribe an AWS Lambda function to the SQS queue.

AWS 100
article thumbnail

How to Shift from Data Science to Data Engineering

ODSC - Open Data Science

This individual is responsible for building and maintaining the infrastructure that stores and processes data; the kinds of data can be diverse, but most commonly it will be structured and unstructured data. They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable.

article thumbnail

Exploring the AI and data capabilities of watsonx

IBM Journey to AI blog

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access. Integrations between watsonx.data and AWS solutions include Amazon S3, EMR Spark, and later this year AWS Glue, as well as many more to come.

AI 62
article thumbnail

40 Must-Know Data Science Skills and Frameworks for 2023

ODSC - Open Data Science

Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed. This pushes into big data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.