AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. In this example, we searched for columns in our data lake that have similar Column Names ( payload type ) to district ( payload ).

Data Lake 97

Data Lake Deep Learning Interactive Machine Learning 97

CIO Business Intelligence

OCTOBER 4, 2023

At the lowest layer is the infrastructure, made up of databases and data lakes. We’ve been working on this for over a decade, including transformer-based deep learning,” says Shivananda. PayPal’s deep learning models can be trained and put into production in two weeks, and even quicker for simpler algorithms.

Digital Transformation 132

Digital Transformation Deep Learning Data Lake Risk 132

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms.

Cost-Benefit 138

Cost-Benefit Data Lake Software Machine Learning 138

CIO Business Intelligence

MAY 23, 2022

The traditional approach for artificial intelligence (AI) and deep learning projects has been to deploy them in the cloud. Different companies approach this from different angles, and some will naturally gravitate to cloud, based on where their data sets are created and live,” he says.

Cost-Benefit 98

Cost-Benefit Experimentation Data Lake Deep Learning 98

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. Introduction. For AWS this means at least P3 instances. P2 GPU instances are not supported.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

Jen Stirrup

MAY 5, 2020

Azure allows you to protect your enterprise data assets, using Azure Active Directory and setting up your virtual network. Other technologies, such as Azure Data Factory, can help process large amounts of data around in the cloud. So, Azure Databricks connects to many different data sources. Azure Data Lake Store.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Just starting out with analytics?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

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

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

CIO Business Intelligence

MARCH 13, 2024

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%). Le reti neurali sono il modello di machine learning più utilizzato oggi.

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

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

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

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

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

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

DataRobot Blog

MARCH 7, 2023

The DataRobot AI Platform seamlessly integrates with Azure cloud services, including Azure Machine Learning, Azure Data Lake Storage Gen 2 (ADLS), Azure Synapse Analytics, and Azure SQL database. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

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 89

Insurance Visualization Data Lake Metrics 89

KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

Data Science 159

Data Science Machine Learning Analytics Data Lake 159

Domino Data Lab

APRIL 3, 2019

Data coming from machines tends to land (aka, data at rest ) in durable stores such as Amazon S3, then gets consumed by Hadoop, Spark, etc. Somehow, the gravity of the data has a geological effect that forms data lakes. DG emerges for the big data side of the world, e.g., the Alation launch in 2012.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Alation

APRIL 14, 2022

Pushing data to a data lake and assuming it is ready for use is shortsighted. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

Metadata 59

Metadata Data Governance Data-driven Modeling 59

IBM Big Data Hub

OCTOBER 16, 2023

Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection. The platform has three powerful components: the watsonx.ai

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

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 118

Data Warehouse Visualization Cost-Benefit Data-driven 118

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

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 90

Statistics Data Warehouse Metadata Data Lake 90