O'Reilly Media - Ideas

MARCH 6, 2019

Artificial Intelligence for Big Data , April 15-16. IoT Fundamentals , April 4-5. Python Data Handling: A Deeper Dive , April 5. Microservice Fundamentals , April 15. Microservice Collaboration , April 16. Domain-Driven Design and Event-Driven Microservices , May 14-15. Clean Code , April 2.

Course 15

Course Artificial Inteligence Training Machine Learning 15

Cloudera

FEBRUARY 4, 2019

One of the most promising technology areas in this merger that already had a high growth potential and is poised for even more growth is the Data-in-Motion platform called Hortonworks DataFlow (HDF). CDF, as an end-to-end streaming data platform, emerges as a clear solution for managing data from the edge all the way to the enterprise.

IoT 73

IoT Open Source Analytics Retail 73

Hu's Place - HitachiVantara

JANUARY 3, 2019

Trend 3: Increasing Data Requirements Will Push Companies to The Edge with Data Enterprise boundaries are extending to the edge – where both data and users reside, and multiple clouds converge. Applications are becoming more modular, leveraging containers and microservices as well as virtualization and bare metal.

Trends 86

Trends Artificial Inteligence Machine Learning Data Center 86

Altexsoft

MARCH 30, 2020

But such improvements require significant investments in IT infrastructure and expertise — namely, in industrial IoT (IIOT) sensors, analytics software with machine learning capabilities, services of data scientists and IT specialists, staff training. Splunk , an industrial analytical tool already integrated with leading IoT platforms.

Artificial Inteligence 72

Artificial Inteligence Machine Learning Technical Review IoT 72

Confluent

SEPTEMBER 26, 2019

Prior to Rockset, Shruti led product management for Oracle Cloud, with a focus on AI, IoT, and blockchain. Kai’s main area of expertise lies within the fields of big data analytics, machine learning, integration, microservices, Internet of Things, stream processing, and blockchain.

Analytics 21

Analytics Serverless Blockchain Microservices 21

Tandem

APRIL 2, 2024

With the ever-expanding set of emerging technologies — big data, machine learning (ML), artificial intelligence (AI), next-gen user experiences (UI/UX), edge computing, the Internet-of-things (IoT), microservices, and Web3 — there is a huge surface area to address.

UI/UX 59

UI/UX Software Weak Development Team Artificial Inteligence 59

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

Linux Academy

JANUARY 26, 2019

Compute- and storage-intensive applications find their way to the cloud because of the need to scale so large that on-premises data centers are simply no longer feasible. Consumers will soon go beyond smartphones and tablets and start using wearables, connected cars, and other IoT devices more than ever before.

Cloud 60

Cloud Artificial Inteligence Data Center Linux 60

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 59

Course Training Artificial Inteligence Machine Learning 59

Confluent

FEBRUARY 6, 2019

And you can use it in any environment: in the cloud, in on-prem datacenters or at the edges, where IoT devices are. Say you wanted to build one integration pipeline from MQTT to Kafka with KSQL for data preprocessing, and use Kafka Connect for data ingestion into HDFS, AWS S3 or Google Cloud Storage, where you do the model training.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Altexsoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. It offers high throughput, low latency, and scalability that meets the requirements of Big Data. process data in real time and run streaming analytics.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Mobilunity

MARCH 25, 2025

Python also excels in automation and building web applications, Data Science, ML, and even developing IoT systems. Integration with Emerging Technologies : Python’s versatility allows it to integrate seamlessly with cutting-edge technologies like IoT and quantum computing, making it a valuable language for upcoming innovations.

Software Review 40

Software Review Software Development Software Development 40

O'Reilly Media - Ideas

APRIL 3, 2019

Data science and data tools. Apache Hadoop, Spark, and Big Data Foundations , April 22. Data Structures in Java , May 1. Cleaning Data at Scale , May 13. Big Data Modeling , May 13-14. Fundamentals of Data Architecture , May 20-21. IoT Fundamentals , May 16-17.

Course 64

Course Artificial Inteligence Training Google Cloud 64

Datica

FEBRUARY 11, 2020

Cloud native – orchestrating containers as part of a microservices architecture – is a departure from traditional application design. Kubernetes and other cloud native technologies enable higher velocity software development at a lower cost than traditional infrastructure. Cost to attend: Ultimate Pass: $799. 1-Day pass: $319.

Conference 52

Conference Technical Review Healthcare Microservices 52

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

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. Embrace AIOps (AI operations) to support multi-cloud and microservices.

Artificial Inteligence 130

Artificial Inteligence Artificial Intelligence Machine Learning Technical Review 130

Trigent

APRIL 14, 2022

With upcoming 5G rollouts, massive IoT networks, mmWave, and network slicing requirements, their cloud and edge capabilities will be of an entirely different scale. AIOps is a set of methods or practices that makes rapid data processing possible for vast volumes of data, which then feed into an ML engine to predict issues.

Enterprise 52

Enterprise Technology Artificial Inteligence IoT 52

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. In some cases, this might well be a valid conclusion.

System 52

System Weak Development Team Microservices Off-The-Shelf 52

Altexsoft

JUNE 20, 2019

The scalability, where data is spread out across a distributed network of manageable servers is one of the MongoDB’s essences. It becomes even more important for enterprises operating big data applications. On top of that, the database is able to allocate data across a cluster of machines. How can it help you?

Systems Review 85

Systems Review System Software Review Open Source 85

Trigent

MARCH 24, 2021

74% of CIOs were reportedly using cloud-native technologies, including microservices, containers, and Kubernetes, and 61% said these environments changed every minute or less. Artificial intelligence, machine learning, big data have all been spoken about extensively and form the very backbone of AIOps. What is AIOps?

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning Infrastructure 52

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

HNAS provides a transparent data migrator for block and file data to private and public clouds and integrates with HCP object store. HCP, Hitachi Content Platform, lets users securely move data to, from, and among multiple cloud services, and better manage use cases including data governance, IoT, and big data.

Cloud 49

Cloud AWS Open Source Data Center 49

Mentormate

APRIL 15, 2024

Whether creating dynamic websites with JavaServer Pages (JSP) or building scalable microservices with Spring Boot, Java provides developers the tools to tackle various projects efficiently. Java offers various tools and frameworks that cater to diverse development needs, from developing web applications to building enterprise-level systems.

Software Review 52

Software Review Telecommunications Technical Review Scalability 52

Trigent

MARCH 24, 2021

74% of CIOs were reportedly using cloud-native technologies, including microservices, containers, and Kubernetes, and 61% said these environments changed every minute or less. Artificial intelligence, machine learning, big data have all been spoken about extensively and form the very backbone of AIOps. What is AIOps?

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning Technical Review 52

Mobilunity

FEBRUARY 25, 2025

It shines in complex projects involving big data, AI, machine learning, automation, and robust backends. Commonly used for building scalable web apps, IoT solutions, and e-commerce platforms. Its also the go-to language for scientific computing, government applications, and big data solutions. What is Python?

Technical Review 40

Technical Review Technology Software Review Artificial Inteligence 40

Instaclustr

OCTOBER 14, 2019

The conference spreads over 4 days next week with a great choice of presentations in multiple tracks including: Cassandra, IoT, Geospatial, Streaming, Machine Learning, and Observability! IoT, geospatial, ML, streaming, etc.), Processing IoT Data from End to End with MQTT and Apache Kafka—Kai Waehner. Kai Waehner.

Technical Review 36

Technical Review Technology Report Open Source 36

Instaclustr

OCTOBER 14, 2019

The conference spreads over 4 days next week with a great choice of presentations in multiple tracks including: Cassandra, IoT, Geospatial, Streaming, Machine Learning, and Observability! I attended this talk as I’m from a Middleware background, and I’m very interested in trends around microservices and integration. Kai Waehner.

Technical Review 28

Technical Review Technology Report Open Source 28

Existek

JANUARY 11, 2022

Along with meeting customer needs for computing and storage, they continued extending services by presenting products dealing with analytics, Big Data, and IoT. The next big step in advancing Azure was introducing the container strategy, as containers and microservices took the industry to a new level.

Azure 52

Azure AWS Cloud How To 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

Confluent

FEBRUARY 13, 2019

Do I need to use a microservices framework? Distributed object (RPC sync), service-oriented architecture (SOA), enterprise service bus (ESB), event-driven architecture (EDA), reactive programming to microservices and now FaaS have each built on the learnings of the previous. Do I need to use a microservices framework?

Architecture 92

Architecture Programming Microservices Serverless 92

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 10

Conference Data Data Engineering Big Data 10

Altexsoft

MARCH 24, 2021

They enable interoperability or smooth data exchange between health systems and create fertile ground for telehealth app development as they. Built in the IBM Cloud, MyTelemedicine platform leverages powerful APIs that can be integrated with most EHR systems, mobile apps, IoT devices, and wearables within a couple of weeks.

Tools 69

Tools Healthcare Insurance Video 69