TechCrunch

OCTOBER 7, 2021

The idea behind using synthetic data sets is that it lets an organization remove the risk of data leaking that might contain personal information or other kinds of sensitive data. They could see that the longer-term issue would be a growing need and priority for data privacy. But humans are not meant to be mined.”

Artificial Inteligence 246

Artificial Inteligence Technical Review Engineering Data 246

Capgemini

MARCH 16, 2022

technologies (AI & analytics, cloud and edge computing, cybersecurity, 5G, IoT, and data engineering) are converging at speed. Intelligent automation : Having data alone is only half the challenge. In the Factory of the Future, Intelligent Industry 4.0

Industry 98

Industry IoT Technical Review Automotive 98

CIO

FEBRUARY 14, 2023

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. AI is the perception, synthesis, and inference of information by machines, to accomplish tasks that historically have required human intelligence.

Artificial Inteligence 290

Artificial Inteligence Strategy Data Machine Learning 290

Cloudera

NOVEMBER 1, 2022

A quick trip in the congressional time machine to revisit 2017’s Modernizing Government Technology Act surfaces some of the most salient points regarding agencies’ challenges: The federal government spends nearly 75% of its annual information technology funding on operating and maintaining existing legacy information technology systems.

Cloud 87

Cloud Government Storage Analytics 87

Trigent

NOVEMBER 3, 2022

Thankfully, it’s now a game for new technologies and leveraging structured and unstructured data like no other. The future of the global supply chain market lies in IoT, integrated solutions, data, and mobility. Connected logistics devices generate a massive amount of data.

Analytics 52

Analytics Data IoT Trends 52

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

Altexsoft

JUNE 14, 2021

Lemonade is a US insurance company that uses Maya – an AI-powered bot, to collect and analyze customer data. Maya acts as a virtual assistant that gets information, provides quotes, and handles payments. First, the customer needs to provide all information about the car. You’ll need a data engineering team for that.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

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.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

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 83

Innovation Data Technical Review Artificial Inteligence 83

Altexsoft

AUGUST 25, 2020

What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Big data is tons of mixed, unstructured information that keeps piling up at high speed. Big data processing.

Big Data 75

Big Data Data Engineering Engineering Data 75

Cloudera

DECEMBER 20, 2022

Today, the costs of sensors, data capture, and information storage have significantly decreased and are one tenth of what they were 10 years ago, leading to the proliferation of data that enables advanced analytics-driving efficiencies. Explore operational efficiencies with our Federated Learning Machine Learning Prototype.

Energy 81

Energy Analytics Data Machine Learning 81

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

DataRobot

MARCH 10, 2022

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). Python is unarguably the most broadly used programming language throughout the data science community. IoT Empowered Assembly Lines: Predictive Maintenance. More Information.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

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

Altexsoft

APRIL 13, 2023

Besides, it means having information about your suppliers, customers, carriers, and other partners, as well as about your internal processes all along the line. It means having information about their origin, journey, ownership, certifications, etc., It’s up to you which information to share, how, with whom, how often, and so on.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

TIBCO - Connected Intelligence

DECEMBER 1, 2020

LeadMind uses analytics, the cloud, and embedded IoT sensors to create over 20 analytics applications, or “train-alytics”. It is a combination of advanced analytics in partnership with TIBCO and CAF’s engineering expertise to maximize the benefit for train operations and optimize maintenance. Click To Tweet.

Training 34

Training Transportation Analytics IoT 34

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. Discover training, hiring, and career opportunities for data professionals. Data scientists. Data engineers. Why You Should Attend. Product managers.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

Cloudera

JANUARY 20, 2021

Managing the collection of all the data from all factories in the manufacturing process is a significant undertaking that presents a few challenges: Difficulty assessing the volume and variety of IoT data: Many factories utilize both modern and legacy manufacturing assets and devices from multiple vendors, with various protocols and data formats.

Data 107

Data Artificial Inteligence Analytics Machine Learning 107

Altexsoft

JULY 23, 2020

It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. MLOps lies at the confluence of ML, data engineering, and DevOps.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Cloudera

JANUARY 19, 2018

The blog finishes by providing concrete examples of how Cloudera customers are delivering strategic functionality like recommendation engines, predictive maintenance, and IoT workflows – all with machine learning at their core. . General Data Protection Regulation (GDPR) and Data Science.

Artificial Inteligence 45

Artificial Inteligence Machine Learning Big Data IoT 45

ParkMyCloud

DECEMBER 11, 2020

Coursera includes a number of free courses including topics in Machine Learning, Architecting, Data Engineering, Developing Applications, and the list goes on. . We picked the 7 above for their reliability, variety, quality, and range of information. Plural Sight.

Google Cloud 97

Google Cloud Training Resources Cloud 97

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

Touchless Claims Will Become A Reality: Thanks to AI & ML along with intelligent data engineering, the insurers will be able to embrace touchless claims enabling the purchase of policies, first-notice-of-loss (FNOL) to the settlement without any human intervention, providing enhanced claim efficiencies and greater customer experience.

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. Sales region: Northern California.

Analytics 20

Analytics Data IoT Analysis 20

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. Each of those were associated with blockers, real and perceived. “It

Artificial Inteligence 334

Artificial Inteligence Analytics Artificial Intelligence Machine Learning 334

Altexsoft

FEBRUARY 8, 2021

These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development. Monitoring production performance. Cost control. Intermodal transport optimization.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Apiumhub

SEPTEMBER 20, 2023

Tech Conferences Compass Tech Summit – October 5-6 Compass Tech Summit is a remarkable 5-in-1 tech conference, encompassing topics such as engineering leadership, AI, product management, UX, and data engineering that will take place on October 5-6 at the Hungarian Railway Museum in Budapest, Hungary.

Conference 96

Conference Artificial Inteligence UI/UX Machine Learning 96

Altexsoft

MARCH 16, 2021

These devices are used to collect tons of various health and fitness-related data, such as daily activity, pulse, temperature, sleep patterns, and so on, all that in real time. But what happens to all the massive amounts of data from all these wearables and other medical and non-medical devices? Big data infrastructure in a nutshell.

Big Data 116

Big Data Healthcare Applications Data 116

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Data availability. What is ELT?

Tools 52

Tools Software Review Systems Review Testing 52

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. Fleet maintenance software features.

Software Review 52

Software Review Technical Review Software Technology 52

ParkMyCloud

MAY 29, 2019

A BI analyst has strong skills in database technology, analytics, and reporting tools and excellent knowledge and understanding of computer science, information systems or engineering. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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. They focus much attention on advancing user experiences utilizing AI, robotics, machine learning, IoT, etc. . Development Operations Engineer $122 000.

Azure 52

Azure AWS Cloud How To 52

Altexsoft

MARCH 31, 2020

A data pipeline is a set of tools and activities for moving data from one system, with its method of data storage and processing, to another system in which it can be stored and managed differently. Imagine that you’re gathering various data that shows how people engage with your brand. Data pipeline components.

Data 76

Data Storage Analytics Data Center 76

Cloudera

FEBRUARY 19, 2018

Any data source should be integrated with a company-wide data catalog to simplify governance, finding relevant data sets, and implementing data management strategies including end-of-life scenarios. Breaking down data silos. Silos are good for storing grain, not data.

Data 46

Data Government Big Data Compliance 46

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. Chief Information Officer (CIO). That’s why you may come across the position of Chief Digital Information Officer.

CTO 52

CTO Organization Technical Review Culture 52

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

Today, data integration is moving closer to the edges – to the business people and to where the data actually exists – the Internet of Things (IoT) and the Cloud. 4 Data and analytics leaders, CDOs, and executives will increasingly work together to develop creative ways for data assets to generate new revenue streams.

Analytics 40

Analytics Artificial Inteligence Data Machine Learning 40