CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. If you want to tap into the opportunity that big data presents, you want to be there. Data scientists. Data engineers. Product managers.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 82

Innovation Data Technical Review Artificial Inteligence 82

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Artificial Inteligence 106

Artificial Inteligence Machine Learning Scalability Data Engineering 106

Hu's Place - HitachiVantara

JANUARY 3, 2019

In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources. More focus will be on the operational aspects of data rather than the fundamentals of capturing, storing and protecting data.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , May 20. First Steps in Data Analysis , May 20. Data Analysis Paradigms in the Tidyverse , May 30.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Coforge

AUGUST 31, 2020

The drastic shift from traditional and orthodox system frameworks and operations can be unarguably attributed to the influx of intelligent technologies such as Artificial Intelligence, Machine Learning, Big Data, Blockchain/DLT led smart contracts, and widespread usage of cloud systems. .

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

Altexsoft

JANUARY 22, 2020

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

Big Data 98

Big Data Tools Data Storage 98

CIO

OCTOBER 18, 2023

German healthcare company Fresenius Medical Care, which specializes in providing kidney dialysis services, is using a combination of near real-time IoT data and clinical data to predict one of the most common complications of the procedure.

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

ParkMyCloud

JANUARY 17, 2020

Display a basic understanding of core AWS services, uses, and basic AWS architecture best practices. Design and maintain network architecture for all AWS services. AWS Certified Big Data – Speciality. For individuals who perform complex Big Data analyses and have at least two years of experience using AWS.

Google Cloud 9

Google Cloud Azure AWS Cloud 9

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Cost control. Shipment tracking and vehicle maintenance.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

O'Reilly Media - Ideas

MARCH 6, 2019

Artificial Intelligence for Big Data , April 15-16. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. Foundational Data Science with R , March 26-27. Real-Time Data Foundations: Flink , April 17.

Course 10

Course Artificial Inteligence Training Microservices 10

Altexsoft

AUGUST 22, 2022

In this post, we’ll attempt to explain the idea behind a data fabric, its architectural building blocks, the benefits it brings, and ways to approach its implementation. What is data fabric? to provide a unified view of all enterprise data. Data fabric architecture example. Data fabric vs data mesh.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

Altexsoft

OCTOBER 24, 2019

We will define how enterprise warehouses are different from the usual ones, what types of data warehouses exist, and how they work. The focus of this material is to provide information about the business value of each architectural and conceptual approach to building a warehouse. What is an Enterprise Data Warehouse?

Architecture 50

Architecture Enterprise Data Technical Review 50

Apiumhub

APRIL 5, 2022

M2- Data Engineering Stage: Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Presentations by some of the leading experts, researchers and practitioners in the area.

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Kafka architecture. Kafka cluster architecture. Kafka cluster and brokers. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

FEBRUARY 22, 2022

Such an approach requires a great deal of investment since a whole ecosystem has to be created, including IoT sensors installation, acquiring specialized software, creating and maintaining machine learning (ML) models, engaging IT and data science specialists , and so on. Collecting data from connected sensors and external sources.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Hu's Place - HitachiVantara

MARCH 18, 2019

City of Istanbul Governorship: Safe, Smart Campus The challenge was to secure the governorship campus and include multiple existing video and IoT systems. This also enabled the data science team, which included IT, data engineers and business analysts with the tools for data preparation and operationalize algorithms.

Healthcare 61

Healthcare Tourism Systems Review Energy 61

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. This requires a new architecture capable of true scale and speed.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Virtualization 69

Virtualization Tools Data Architecture 69

TIBCO - Connected Intelligence

AUGUST 10, 2020

Your data demands, like your data itself, are outpacing your data engineering methods and teams. You’ll discover that they all have identified data virtualization as a must-have addition to your data integration tooling and a critical enabler to a more modern, distributed data architecture.

Virtualization 69

Virtualization Data How To Data Engineering 69

Altexsoft

OCTOBER 26, 2022

Today, the CIO’s focus is primarily on a company’s IT architecture and infrastructure. This can be anything from CRMs to AI-powered chatbots to IoT systems. To make better digital transformation decisions, a CDO must know how modern technologies work, including such areas as machine learning, data engineering , and IoT.

CTO 52

CTO Organization Technical Review Culture 52

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

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake data management processes. Ensure data accessibility.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Kentik

DECEMBER 15, 2016

IDC’s recognition of Kentik was two-fold, based not only on the fact that we’re SaaS/cloud-based (in fact, we also can deploy our big data solution on an on-premises cluster) but also on the deep capabilities of our Kentik Detect product. A fundamentally different architecture is required. Why Kentik? Siloes Be Gone!

UI/UX 40

UI/UX Innovation Big Data Network 40

Altexsoft

DECEMBER 9, 2020

Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Predictive analytics creates probable forecasts of what will happen in the future, using machine learning techniques to operate big data volumes. Data warehouse architecture. Analytics maturity model.

Analytics 102

Analytics Technical Review Technology Applications 102

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

Big Data 52

Big Data Analytics Data Analysis 52

Cloudera

MAY 18, 2021

The intent of this article is to articulate and quantify the value proposition of CDP Public Cloud versus legacy IaaS deployments and illustrate why Cloudera technology is the ideal cloud platform to migrate big data workloads off of IaaS deployments. data streaming, data engineering, data warehousing etc.),

Cloud 86

Cloud Technical Review Storage Backup 86

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

Data 59

Data Technical Review Software Review Artificial Inteligence 59

Datavail

SEPTEMBER 8, 2022

Big data presents challenges in terms of volume, velocity, and variety—but that doesn’t mean you have to suffer from a bloated IT ecosystem to address these challenges. In fact, many businesses can realize significant advantages from streamlining their data integration pipelines, trimming away unnecessary tools and services.

Data 40

Data Nonprofit Quality Assurance Education 40