Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Altexsoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

O'Reilly Media - Ideas

MAY 1, 2019

Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. AI and machine learning.

Course 46

Course Training Artificial Inteligence Machine Learning 46

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

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. This shift in attitude and expectations needed to come top down and bottom up,” he says.

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

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

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

CIO

NOVEMBER 29, 2022

By George Trujillo, Principal Data Strategist, DataStax Innovation is driven by the ease and agility of working with data. Increasing ROI for the business requires a strategic understanding of — and the ability to clearly identify — where and how organizations win with data.

Organization 265

Organization Technical Review Data Artificial Inteligence 265

Altexsoft

JUNE 25, 2019

Being at the top of data science capabilities, machine learning and artificial intelligence are buzzing technologies many organizations are eager to adopt. 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.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

OCTOBER 29, 2020

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.

Data 111

Data Machine Learning Artificial Inteligence Analytics 111

Apiumhub

SEPTEMBER 20, 2023

From software architecture to artificial intelligence and machine learning, ​​these conferences offer unparalleled insights, networking opportunities, and a glimpse into the future of technology. Learn more about the speakers and check out their schedule by visiting their site here. Interested in attending?

Conference 97

Conference Artificial Inteligence UI/UX Machine Learning 97

Altexsoft

FEBRUARY 8, 2021

To support the planning process, predictive analytics and machine learning (ML) techniques can be implemented. We have previously described demand forecasting methods and the role of machine learning solutions in a dedicated article. Comparison between traditional and machine learning approaches to demand forecasting.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. Continuing the journey toward true business agility initiated in the software realm. Denis Gagne Trisotech [link]. Max Pucher Isis Papyrus [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

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

DataRobot

APRIL 1, 2018

1) People and machines come together to create a more powerful and agile experience. Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. 2) Line of business is taking a more active role in data projects.

Analytics 40

Analytics Artificial Inteligence Data Machine Learning 40

Altexsoft

OCTOBER 26, 2022

To enable this conversion, a CDO uses digital information and modern technologies such as the cloud, the Internet of Things , mobile apps, social media, machine learning-based products, and digital marketing. Cultural changes will also include the introduction of new forms of work and the development of agile skills among employees.

CTO 52

CTO Organization Technical Review Culture 52

TIBCO - Connected Intelligence

DECEMBER 20, 2021

The Unify Portfolio Highlights Breakthroughs in Data Integration and Lays the Foundation for the Future of Data Fabric. Enhancements in the Unify portfolio address organizations’ data management challenges head-on, empowering the business to assemble an agile data fabric, unrestricted by siloed data, on any cloud platform.

Innovation 26

Innovation Analytics Virtualization Cloud 26

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. Introducing data engineering and data science expertise.

Analytics 102

Analytics Technical Review Technology Applications 102

CIO

AUGUST 3, 2022

When Cargill started putting IoT sensors into shrimp ponds, then CIO Justin Kershaw realized that the $130 billion agricultural business was becoming a digital business. To help determine where IT should stop and IoT product engineering should start, Kershaw did not call CIOs of other food and agricultural businesses to compare notes.

SDLC 347

SDLC IoT Machine Learning Artificial Inteligence 347

Agile Engine

DECEMBER 27, 2023

Case study: leveraging AgileEngine as a data solutions vendor 11. Key takeaways Any organization that operates online and collects data can benefit from a data analytics consultancy, from blockchain and IoT, to healthcare and financial services The market for data analytics globally was valued at $112.8

Big Data 52

Big Data Analytics Data Analysis 52