Hu's Place - HitachiVantara

NOVEMBER 11, 2018

This will be a blend of private and public hyperscale clouds like AWS, Azure, and Google Cloud Platform. Private clouds are not simply existing data centers running virtualized, legacy workloads. The term “hyperscale” is used by Gartner to refer to Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

Cloud 78

Cloud Google Cloud Azure AWS 78

Cloudera

MAY 18, 2021

Finally, IaaS deployments required substantial manual effort for configuration and ongoing management that, in a way, accentuated the complexities that clients faced deploying legacy Hadoop implementations in the data center. Experience configuration / use case deployment: At the data lifecycle experience level (e.g.,

Cloud 86

Cloud Technical Review Storage Backup 86

O'Reilly Media - Ideas

JUNE 4, 2019

Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19. First Steps in Data Analysis , July 22.

Course 93

Course Training Artificial Inteligence Software Review 93

Cloudera

MAY 13, 2021

Fixed Reports / Data Engineering jobs . Often mission-critical to the various lines of business (risk analytics, platform support, or data engineering), which hydrate critical data pipelines for downstream consumption. Fixed Reports / Data Engineering Jobs. Data Engineering jobs only.

Data Engineering 73

Data Engineering Cloud Weak Development Team Resources 73

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data lakes are mostly used by data scientists for machine learning projects.

Data 76

Data Storage Analytics Data Center 76

Cloudera

JUNE 15, 2021

We can run the quickstart environment, which is a Docker container we can run locally or within a pipeline, or we can install the dependencies on a Linux machine in our data center infrastructure. If you are using VMs in Azure or AWS the Default credentials will be automatically collected from your local user profile (.aws

Cloud 86

Cloud AWS Azure Linux 86

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview.

Analytics 20

Analytics Data IoT Analysis 20

O'Reilly Media - Ideas

JUNE 5, 2019

Understanding Data Science Algorithms in R: Regression , July 12. Cleaning Data at Scale , July 15. Scalable Data Science with Apache Hadoop and Spark , July 16. Effective Data Center Design Techniques: Data Center Topologies and Control Planes , July 19. First Steps in Data Analysis , July 22.

Course 66

Course Training Artificial Inteligence Software Review 66

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

DataRobot

SEPTEMBER 14, 2021

AI Cloud brings together any type of data, from any source, giving you a unique, global view of insights that drive your business. All of this is part of a unified, integrated platform spanning data engineering, machine learning, decision intelligence, and continuous AI – the entire AI lifecycle.

Cloud 52

Cloud Machine Learning Artificial Inteligence Data Center 52

TIBCO - Connected Intelligence

APRIL 22, 2021

Leading cloud providers such as AWS, Microsoft Azure, and Google Cloud have developed world-class cloud data centers whose sustainability levels are difficult for organizations like yours to match because: They optimize server performance and usage elastically with demand, powering down what isn’t needed.

Sustainability 46

Sustainability Virtualization Data Energy 46

Cloudera

SEPTEMBER 1, 2020

Although not elaborated on in this blog post, it is possible to use a CDP Data Hub Data Engineering cluster for pre-processing data via Spark, and then post to Solr on DDE for indexing and serving. Built-in Cost Efficiency . The advantage with cloud is of course the transient allocation of resources.

Data 71

Data Backup Disaster Recovery Storage 71

DataRobot

FEBRUARY 2, 2022

DataRobot enables entire teams — from data scientists to data engineers and from IT to business users — to collaborate on a unified platform. By partnering with major cloud companies like AWS, Google Cloud, Azure, and VMware, DataRobot helps customers harness the power of their data wherever it lives.

Cloud 52

Cloud Innovation Google Cloud Data Center 52

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Its very architecture is centered around the idea of painless expansion the moment your business needs it. A single cluster can span across multiple data centers and cloud facilities.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

MARCH 1, 2023

Companies can no longer protect all of their IT systems behind a firewall; many of the servers are running in a data center somewhere, and IT staff has no idea where they are or even if they exist as physical entities. Data engineering was the dominant topic by far, growing 35% year over year.

Trends 144

Trends Technical Review Technology Software Review 144

O'Reilly Media - Ideas

JANUARY 25, 2021

There’s been a lot of discussion about operations culture (the movement frequently known as DevOps), continuous integration and deployment (CI/CD), and site reliability engineering (SRE). Cloud computing has replaced data centers, colocation facilities, and in-house machine rooms. Docker and Kubernetes versus Chef and Puppet.

Programming 145

Programming Cloud Artificial Inteligence Machine Learning 145

CIO

NOVEMBER 14, 2024

Recently, we sponsored a study with IDC* that surveyed teams of data scientists, data engineers, developers, and IT professionals working on AI projects across enterprises worldwide. To tackle this challenge, we are focused on simplifying and unifying data storage to support better data access.

Enterprise 149

Enterprise Survey Storage Study 149