Apiumhub

APRIL 1, 2021

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by by EMC Education Services. The whole data analytics lifecycle is explained in detail along with case study and appealing visuals so that you can see the practical working of the entire system.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Altexsoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. Source: The Wall Street Journal. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Big Data 59

Big Data Data Google Cloud Storage 59

The Cipher Brief

JUNE 2, 2021

The government’s information architecture will have to be re-configured to meet the challenge posed by the Chinese state. Machine learning and natural language processing systems are required to do this at scale: the Chinese Knowledge Resource Database, for example, has over 71 million academic journals. Innovation Activity.

Organization 35

Organization Journal Government Artificial Inteligence 35

Confluent

FEBRUARY 6, 2019

The serving and monitoring infrastructure need to fit into your overall enterprise architecture and tool stack. Data scientists combining Python and Jupyter with scalable streaming architectures. Data scientists use tools like Jupyter Notebooks to analyze, transform, enrich, filter and process data.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

Dion Hinchcliffe's Web 2.0 Blog

SEPTEMBER 12, 2011

The problem lies in our classical views of enterprise architecture and business architecture both. and SOA is one that I deeply explored in the 2005-2007 timeframe, and my ideas on this even made the cover story of the SOA/Web Services Journal at one point. This fractal aspect of user systems, Web 2.0, But we’ve learned.

Social 65

Social SOA Technical Advisors Architecture 65

Altexsoft

OCTOBER 22, 2021

Image source: Horse Journals. Typical architecture of deep learning neural nets. The input data goes through multiple processing layers of artificial neurons piled up on top of one another to provide the output. Typical architecture of deep neural networks. More data — better performance.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence .Net Machine Learning 52

CIO

OCTOBER 18, 2023

Putting data to work to improve health outcomes “Predicting IDH in hemodialysis patients is challenging due to the numerous patient- and treatment-related factors that affect IDH risk,” says Pete Waguespack, director of data and analytics architecture and engineering for Fresenius Medical Care North America.

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

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. Data evolution.

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

Confluent

JUNE 26, 2019

In these projects, microservice architectures use Kafka as an event streaming platform. Everybody is talking about creating an agile and flexible architecture with microservices , a term that is used today in many different contexts. What technology should you use to build microservice architectures? Microservices.

Microservices 109

Microservices Software Review Technical Review Architecture 109

d2iq

JANUARY 23, 2023

While some cloud edge infrastructure might be in on-premises data centers, “more of it will be in new edge data centers, embedded in edge devices or even built right into the telecom infrastructure.” Every day, huge amounts of data are generated, streamed, and moved in cloud environments.

Artificial Inteligence 69

Artificial Inteligence Artificial Intelligence IoT Data Center 69

Altexsoft

NOVEMBER 5, 2021

Example of a data dictionary. Source: Journal of AHIMA. Note that if your hospital uses a modern database management system to handle information, a dictionary of “data about the data” will be generated automatically. Amazon also possesses tools to build HIPAA-compliant architecture with AWS services.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

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.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Confluent

OCTOBER 10, 2019

Let’s now take a look at the 10,000-foot view of a robust IoT integration architecture. End-to-end enterprise integration architecture. IoT integration architectures need to integrate the edge (devices, machines, cars, etc.) with the datacenter (on premises, cloud, and hybrid) to be able to process IoT data.

IoT 20

IoT Internet Weak Development Team Scalability 20

The Cipher Brief

SEPTEMBER 20, 2020

Although the IC has invested in advanced analytic tradecraft and big data techniques for other purposes, the IC has made comparatively few and only isolated investments in understanding the needs and behavior of the customers it serves. As a result, the IC is flying blind.

Business Analytics 56

Business Analytics Analytics Metrics Technical Review 56

Bernd Rucker

JULY 18, 2019

I contrasted this to traditional workflow engine architectures using a RDMS in part 1 of this blog post. like a journal in accounting. I apologize to Martin Kleppmann who wrote Please stop calling databases CP or AP, but I think it helps in understanding the architecture of Zeebe).

Scalability 42

Scalability Data Center Data Engineering 42

CTOvision

JULY 14, 2015

Hootenanny crowdsources geospatial data analysis - GCN.com GCN (Today) - Hootenanny crowdsources geospatial data analysis The National Geospatial-Intelligence Agency has publicly released Hootenanny, a software toolkit designed to harness the power of crowdsourced mapping for geospatial big data analytics.

Technical Support 102

Technical Support Transportation Government Analytics 102