Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

Tableau 98

Tableau Data Quality Analytics Analytics 98

IBM Journey to AI blog

MAY 9, 2023

Today is a revolutionary moment for Artificial Intelligence (AI). It offers its users advanced machine learning, data management , and generative AI capabilities to train, validate, tune and deploy AI systems across the business with speed, trusted data, and governance.

AI 110

AI AI Data Warehouse Machine Learning 110

AWS Machine Learning Blog

MAY 31, 2024

This means that individuals can ask companies to erase their personal data from their systems and from the systems of any third parties with whom the data was shared. Data preparation Before creating a knowledge base using Knowledge Bases for Amazon Bedrock, it’s essential to prepare the data to augment the FM in a RAG implementation.

AWS 126

AWS Machine Learning Machine Learning Database 126

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93

AWS Database ETL AI 93

ODSC - Open Data Science

JUNE 12, 2023

No-code/low-code experience using a diagram view in the data preparation layer similar to Dataflows. Building business-focussed semantic layers in the cloud (the Power BI Service) with data modeling capabilities, such as managing relationships, creating measures, defining incremental refresh, and creating and managing RLS.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

Flipboard

NOVEMBER 24, 2023

JuMa is tightly integrated with a range of BMW Central IT services, including identity and access management, roles and rights management, BMW Cloud Data Hub (BMW’s data lake on AWS) and on-premises databases.

ML 153

ML ML AWS AI 153

IBM Journey to AI blog

JULY 17, 2023

Visual modeling: Delivers easy-to-use workflows for data scientists to build data preparation and predictive machine learning pipelines that include text analytics, visualizations and a variety of modeling methods.

AI 74

AI AI Machine Learning Machine Learning 74

ODSC - Open Data Science

NOVEMBER 19, 2024

Despite the rise of big data technologies and cloud computing, the principles of dimensional modeling remain relevant. This session delved into how these traditional techniques have adapted to data lakes and real-time analytics, emphasizing their enduring importance for building scalable, efficient data systems.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

AWS Machine Learning Blog

NOVEMBER 22, 2023

He highlights innovations in data, infrastructure, and artificial intelligence and machine learning that are helping AWS customers achieve their goals faster, mine untapped potential, and create a better future.

AWS 129

AWS ML ML AI 129

AWS Machine Learning Blog

AUGUST 4, 2023

Train a recommendation model in SageMaker Studio using training data that was prepared using SageMaker Data Wrangler. The real-time inference call data is first passed to the SageMaker Data Wrangler container in the inference pipeline, where it is preprocessed and passed to the trained model for product recommendation.

ML 89

ML ML AWS AI 89

Pickl AI

OCTOBER 10, 2024

Informatica’s AI-powered automation helps streamline data pipelines and improve operational efficiency. Common use cases include integrating data across hybrid cloud environments, managing data lakes, and enabling real-time analytics for Business Intelligence platforms.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 5, 2024

Storage Solutions: Secure and scalable storage options like Azure Blob Storage and Azure Data Lake Storage. Key features and benefits of Azure for Data Science include: Scalability: Easily scale resources up or down based on demand, ideal for handling large datasets and complex computations.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022.

SQL 52

SQL ML ML Python 52

AWS Machine Learning Blog

JANUARY 26, 2024

Generative artificial intelligence (AI) applications built around large language models (LLMs) have demonstrated the potential to create and accelerate economic value for businesses. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

AWS 137

AWS ML ML AI 137

AWS Machine Learning Blog

AUGUST 15, 2024

Importing data from the SageMaker Data Wrangler flow allows you to interact with a sample of the data before scaling the data preparation flow to the full dataset. This improves time and performance because you don’t need to work with the entirety of the data during preparation.

ML 119

ML ML Data Preparation AWS 119