Kentik

MARCH 7, 2018

IoT plays a key role in sensing all of the critical elements in the physical world and delivering a continuous feed of sensor data to a Big Data analytics cluster situated in the cloud. Industry 4.0 involves modeling and monitoring the physical world in the digital domain using cyber-physical systems. Industry 4.0

Industry 40

Industry Data Center WAN Big Data 40

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. Apache Hadoop, Spark and Big Data Foundations , June 5. Real-time Data Foundations: Kafka , June 11. SQL Fundamentals for Data , June 12-13. Real-time Data Foundations: Spark , June 13.

Course 45

Course Training Artificial Inteligence Machine Learning 45

OTS Solutions

MAY 2, 2023

Internet of Things (IoT): The Internet of Things has become important in digital transformation. It is a network of interconnected devices that can communicate and exchange data with each other. MLOps increases productivity, Repeatability, Reliability, Auditability, Data, and model quality of machine learning models.

Artificial Inteligence 130

Artificial Inteligence Artificial Intelligence Machine Learning Blockchain 130

O'Reilly Media - Ideas

FEBRUARY 6, 2019

Get hands-on training in machine learning, microservices, blockchain, Python, Java, and many other topics. Machine Learning for IoT , March 20. Data science and data tools. Business Data Analytics Using Python , February 27. Designing and Implementing Big Data Solutions with Azure , March 11-12.

Artificial Inteligence 11

Artificial Inteligence Course Training Artificial Intelligence 11

Altexsoft

FEBRUARY 24, 2023

Containers have become the preferred way to run microservices — independent, portable software components, each responsible for a specific business task (say, adding new items to a shopping cart). Modern apps include dozens to hundreds of individual modules running across multiple machines— for example, eBay uses nearly 1,000 microservices.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

OpenCredo

MAY 14, 2020

A significant factor in this journey has been the ability to automate infrastructure delivery – and as complexity has grown with the adoption of microservices, big data and IOT, this automation has evolved to become more sophisticated. Complexity & DevOps.

System 52

System Weak Development Team Microservices Off-The-Shelf 52

BPM

JANUARY 18, 2019

The microservice movement will reignite the need for orchestration. Some analyst is bound to rename BPM engines to Microservice Orchestration Engines (MOE).wait As we move into a world that is more and more dominated by technologies such as big data, IoT, and ML, more and more processes will be started by external events.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

Hybrid and multi-cloud also provide flexible data management, governance, compliance, availability, and durability. Another aspect of agility is the self-service resources that enables the DevOps culture to run dev/test workloads in the cloud. It eliminates upfront capital costs and avoids the risk of infrastructure vendor lock-in.

Cloud 49

Cloud AWS Azure Data Center 49

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. Stream” itself was No.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8