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 44

Course Training Artificial Inteligence Machine Learning 44

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

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 Data Center Machine Learning 86

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

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 46

Course Artificial Inteligence Training Google Cloud 46

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

Confluent

FEBRUARY 6, 2019

The serving and monitoring infrastructure need to fit into your overall enterprise architecture and tool stack. And you can use it in any environment: in the cloud, in on-prem datacenters or at the edges, where IoT devices are. Data scientists combining Python and Jupyter with scalable streaming architectures.

Artificial Inteligence 106

Artificial Inteligence Machine Learning Scalability Data Engineering 106

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

Confluent

MAY 22, 2019

Through the Internet of Things (IoT), it is also connecting humans to the machines all around us and directly connecting machines to other machines. In light of this, we’ll share an emerging machine-to-machine (M2M) architecture pattern in which MQTT, Apache Kafka ® , and Scylla all work together to provide an end-to-end IoT solution.

IoT 96

IoT Google Cloud Scalability Microservices 96

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

O'Reilly Media - Ideas

MARCH 6, 2019

Artificial Intelligence for Big Data , April 15-16. Managing Enterprise Data Strategies with Hadoop, Spark, and Kafka , April 15. Real-Time Data Foundations: Flink , April 17. Data Pipelining with Luigi and Spark , April 17. Real-Time Data Foundations: Time Series Architectures , April 18.

Course 10

Course Artificial Inteligence Training Machine Learning 10

Trigent

MARCH 29, 2023

Rather it requires a conscious effort to design and develop an architecture that delivers an integrated experience regardless of the distribution partners. This allows InsurTechs to take advantage of additional data available with the distribution partner to personalize the coverage and premiums.

Insurance 95

Insurance Strategy Serverless Big Data 95

Confluent

FEBRUARY 13, 2019

Part 1 of this series discussed why you need to embrace event-first thinking, while this article builds a rationale for different styles of event-driven architectures and compares and contrasts scaling, persistence and runtime models. In this way, we don’t think about solution architecture in just one dimension.

Architecture 89

Architecture Programming Microservices Serverless 89

Confluent

SEPTEMBER 26, 2019

explains in more detail why many new integration architectures leverage Apache Kafka instead of legacy tools like RabbitMQ, ETL, and ESB. bank transactions) to ensure reliable messaging and processing with high availability, exactly once semantics, and zero data loss. Kafka Connect is a core component in event streaming architecture.

Analytics 20

Analytics Serverless Blockchain Microservices 20

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

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 74

IoT Open Source Analytics Retail 74

BPM

JANUARY 18, 2019

Now we’re seeing AI dominating the conversations (without a lot of actual adoption in the early majority), and RPA creating a lot of buzz, though companies adopting it are starting to realize that scaling an RPA based automation architecture is flawed by design. The microservice movement will reignite the need for orchestration.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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

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

Confluent

OCTOBER 10, 2019

The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. A key challenge, however, is integrating devices and machines to process the data in real time and at scale. Confluent MQTT Proxy , which ingests data from IoT devices without needing a MQTT broker.

IoT 20

IoT Internet Weak Development Team Scalability 20

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

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. Kafka architecture.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

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 Azure 49

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.

Technical Review 36

Technical Review Technology Report Open Source 36

Altexsoft

JUNE 20, 2019

Oracle’s multi-model solution allows for accommodating and processing a vast amount of data. Thanks to the recently released multi-tenancy feature, the database architecture now simplifies packing many databases and manage them smoothly. It becomes even more important for enterprises operating big data applications.

Systems Review 85

Systems Review System Software Review Open Source 85

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 Big Data 8

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! A clever architectural trick, leveraging this abstraction, is the use of Proxy Nodes for the Cassandra query path. acts as a buffer), etc.

Technical Review 28

Technical Review Technology Report Open Source 28