Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. Data Ingestion. The raw data is in a series of CSV files. The post NVIDIA RAPIDS in Cloudera Machine Learning appeared first on Cloudera Blog. Introduction.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

CIO Business Intelligence

JULY 10, 2024

Utilizamos Azure Data Factory para el proceso de extracción y ETL, el cual genera un data lake con toda la información consolidada almacenándose en un data warehouse basado en tecnología SQL. Epsilon) y datos en Excel alojados en Sharepoint.

Data Lake 105

Data Lake Big Data Deep Learning Data Warehouse 105

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. models are trained on IBM’s curated, enterprise-focused data lake, on our custom-designed cloud-native AI supercomputer, Vela. All watsonx.ai

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

CIO Business Intelligence

MARCH 13, 2024

Altrettanto importante (e forse più trascurata) è la questione dei big data che servono per addestrare i modelli e il costo connesso. L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%).

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

AWS Big Data

NOVEMBER 15, 2023

With new capabilities for self-service and straightforward builder experiences, you can democratize data access for line of business users, analysts, scientists, and engineers. Hear also from Adidas, GlobalFoundries, and University of California, Irvine.

Data Lake 72

Data Lake Data Warehouse B2B Deep Learning 72

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.

Insurance 98

Insurance Visualization Data Lake Metrics 98

Cloudera

FEBRUARY 4, 2019

Stream Processing – Manage and process multiple streams of real-time data using the most advanced distributed stream processing system – Apache Kafka. Process millions of real-time messages per second to feed into your data lake or for immediate streaming analytics.

IoT 73

IoT Prescriptive Analytics Internet of Things Digital Transformation 73

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

AWS Big Data

MAY 16, 2024

About Amazon Redshift Thousands of customers rely on Amazon Redshift to analyze data from terabytes to petabytes and run complex analytical queries. With Amazon Redshift, you can get real-time insights and predictive analytics on all of your data across your operational databases, data lake, data warehouse, and third-party datasets.

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Data-driven 119

IBM Big Data Hub

JUNE 14, 2023

Traditional AI tools, especially deep learning-based ones, require huge amounts of effort to use. You need to collect, curate, and annotate data for any specific task you want to perform. Sometimes the problem with artificial intelligence (AI) and automation is that they are too labor intensive.

Modeling 84

Modeling Data Lake Enterprise Deep Learning 84

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). in lieu of simply landing in a data lake.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. models are trained on IBM’s curated, enterprise-focused data lake. That’s where the foundation model enters the picture. All watsonx.ai

Modeling 55

Modeling Cost-Benefit Machine Learning Data Lake 55

IBM Big Data Hub

OCTOBER 16, 2023

ML also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. The platform has three powerful components: the watsonx.ai

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

Alation

APRIL 14, 2022

A cloud environment with such features will support collaboration across departments and across common data types, including csv, JSON, XML, AVRO, Parquet, Hyper, TDE, and more. It’s More Important to Know What Your Data Means Than Where It Is. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

AWS Big Data

OCTOBER 25, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Statistics 109

Statistics Data Warehouse Metadata Data Lake 109