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

Mobilunity

DECEMBER 28, 2022

Machine Learning is a rapidly-growing field that is revolutionizing the way businesses work and collect data. The process of machine learning involves teaching computers to learn from data without being explicitly programmed. The Services That Machine Learning Engineers Can Offer.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

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.

Conference 97

Conference Artificial Inteligence UI/UX Machine Learning 97

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

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 20, 2023

The vendor-neutral certification covers topics such as organizational structure, security and risk management, asset security, security operations, identity and access management (IAM), security assessment and testing, and security architecture and engineering.

SCRUM 344

SCRUM Azure AWS Agile 344

Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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. Consolidated data protection.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

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. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

Apiumhub

FEBRUARY 6, 2023

In this event, hundreds of innovative minds, enterprise practitioners, technology providers, startup founders, and innovators come together to discuss ideas on data science, big data, ML, AI, data management, data engineering, IoT, and analytics.

Innovation 83

Innovation Data Machine Learning Artificial Inteligence 83

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 84

Innovation Data Technical Review Artificial Inteligence 84

Trigent

AUGUST 26, 2022

Trigent offers end-to-end consulting services, design, development, and managed services across Infrastructure, Cloud, Mobility, BI, Analytics, Product Engineering, Quality Engineering, IoT, Data Engineering, and Artificial Intelligence.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 52

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

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

Cloudera

NOVEMBER 1, 2022

Through modern data architectures powered by CDP, including Cloudera-enabled data fabric, data lakehouse, and data mesh , DoD agencies can rapidly provision and manage innovative data engineering, data warehouse, and machine learning environments, with access to secured supply chain data stored in CDP Private Cloud.

Cloud 86

Cloud Government Storage Analytics 86

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. Analytics maturity model. Data warehouse architecture.

Analytics 102

Analytics Technical Review Technology Applications 102

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

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. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

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 45

Course Training Artificial Inteligence Machine Learning 45

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

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

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

Mobilunity

MAY 8, 2023

Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone.

Engineering 52

Engineering Data Storage AWS 52

CTOvision

FEBRUARY 23, 2017

Attending is a great way to track the latest in the community, learn (and share) lessons learned and find the most capable technologies ready for enterprise use. 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.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

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

Hu's Place - HitachiVantara

JANUARY 15, 2019

When the formation of Hitachi Vantara was announced, it was clear that combining Hitachi’s broad expertise in OT (operational technology) with its proven IT product innovations and solutions, would give customers a powerful, collaborative partner, unlike any other company, to address the burgeoning IoT market.

Systems Review 72

Systems Review Storage System Software Review 72

Cloudera

MAY 18, 2021

That is accomplished by delivering most technical use cases through a primarily container-based CDP services (CDP services offer a distinct environment for separate technical use cases e.g., data streaming, data engineering, data warehousing etc.) Machine Learning Prototypes. Not available. Not available.

Cloud 84

Cloud Technical Review Storage Backup 84

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. Time and investment. Choosing partners.

Software Review 52

Software Review Technical Review Software Technology 52

Confluent

JUNE 7, 2019

Our data science team uses KSQL to experiment with raw or lifted streams to ultimately deploy new machine learning models ( using custom user-defined functions ) without writing a single line of Java code. The Confluent Platform is an amazing toolbox, which every architect and data engineer should know of and utilize.

Blockchain 91

Blockchain Data Technical Review Software Review 91

Altexsoft

APRIL 13, 2023

“Control towers are the artificial intelligence (AI) of supply chain. Supply chain control tower architecture: main components, integrations, and data sources As we mentioned, an SCCT is typically comprised of multiple components that handle various aspects of supply chain management.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data pipeline components. When do you need a data pipeline?

Data 76

Data Storage Analytics Data Center 76

Altexsoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc. Apache Hadoop.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

JUNE 7, 2021

The system automatically replicates information to prevent data loss in the case of a node failure. Hadoop architecture, or how the framework works. In the former case, the framework is set up on one virtual machine, which is preferable for the evaluation or test phase. No real-time data processing. Processing options.

Big Data 98

Big Data Tools Data Storage 98

O'Reilly Media - Ideas

MARCH 6, 2019

Get hands-on training in machine learning, AWS, Kubernetes, Python, Java, and many other topics. Learn new topics and refine your skills with more than 170 new live online training courses we opened up for March and April on the O'Reilly online learning platform. AI and machine learning.

Course 10

Course Artificial Inteligence Training Microservices 10

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. Today, the CIO’s focus is primarily on a company’s IT architecture and infrastructure. Attract talent.

CTO 52

CTO Organization Technical Review Culture 52

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