InfoQ Culture Methods

DECEMBER 28, 2020

As 2020 is coming to an end, we created this article listing some of the best posts published this year. This collection was hand-picked by nine InfoQ Editors recommending the greatest posts in their domain. It's a great piece to make sure you don't miss out on some of the InfoQ's best content.

Continuous Delivery 94

Continuous Delivery Google Cloud Data Engineering Microservices 94

Dzone - DevOps

OCTOBER 30, 2023

In this article, we explore the synergy between software-based architecture and the development of interoperability solutions for IoT to provide insights relevant to software developers and data engineers. To tackle this challenge head-on, software-based architectures are emerging as powerful solutions.

IoT 95

IoT Architecture Software Data Engineering 95

Progress

DECEMBER 30, 2019

Based on my interactions with thousands of developers in the Progress / Telerik developer tools ecosystem, I wrote a separate article contrasting Kinvey with Firebase. AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

Progress

DECEMBER 30, 2019

Based on my interactions with thousands of developers in the Progress / Telerik developer tools ecosystem, I wrote a separate article contrasting Kinvey with Firebase. AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

InfoQ Culture Methods

JANUARY 19, 2022

In this podcast summary Thomas Betts, Wes Reisz, Shane Hastie, Charles Humble, Srini Penchikala, and Daniel Bryant discuss what they have seen in 2021 and speculate a little on what they hope to see in 2022. Topics explored included: hybrid working and the importance of ethics and sustainability within technology.

Technical Review 97

Technical Review Sustainability Artificial Inteligence Technology 97

InfoQ Culture Methods

DECEMBER 6, 2019

As part of the 2019 end-of-year-summary content, this article collects together a list of recommended presentation recordings from the InfoQ editorial team. By Charles Humble, Ben Linders, Arthur Casals, Manuel Pais, Erik Costlow, Shane Hastie, Shaaron A Alvares, Srini Penchikala, Michael Redlich, Steef-Jan Wiggers, Daniel Bryant.

Data Engineering 52

Data Engineering Architecture Programming System 52

Dzone - DevOps

FEBRUARY 7, 2023

As digital transformation reaches more industries, the number of data points generated is growing exponentially. As such, data integration strategies to collect such large volumes of data from different sources in varying formats and structures are now a primary concern for data engineering teams.

Strategy 98

Strategy Data Data Engineering Analysis 98

Altexsoft

JUNE 29, 2021

This article will focus on the role of a machine learning engineer, their skills and responsibilities, and how they contribute to an AI project’s success. The role of a machine learning engineer in the data science team. Who does what in a data science team. Machine learning engineer vs. data scientist.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

InfoQ Culture Methods

APRIL 18, 2020

At the end of 2019, InfoQ ran a survey of our readers to find out what tools, techniques, and languages they were using. This is a summary of the results. By Charles Humble.

Survey 54

Survey Tools Data Engineering Programming 54

InfoQ Culture Methods

DECEMBER 6, 2019

We take a look back at what we saw on InfoQ in 2019, and think about what the next year might bring. By Charles Humble, Erik Costlow, Arthur Casals, Daniel Bryant, Bruno Couriol, Ben Linders, Shane Hastie.

Software 52

Software Data Engineering .Net Architecture 52

TechCrunch

DECEMBER 10, 2020

” It currently has a database of some 180,000 engineers covering around 100 or so engineering skills, including React, Node, Python, Agular, Swift, Android, Java, Rails, Golang, PHP, Vue, DevOps, machine learning, data engineering and more.

Engineering 325

Engineering Artificial Inteligence Lambda Machine Learning 325

Dzone - DevOps

FEBRUARY 16, 2023

However, in today's era, what's more, important than the data itself is the ability to locate your wanted information among all the overflowing data quickly. So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses.

Data 87

Data ChatGPT Storage Architecture 87

UruIT

OCTOBER 17, 2019

From our experience, we realized that there are great profiles in Bogotá with strong skills in English and technical areas we’re interested in, such as Data Engineering, UX, Devops, and Machine Learning.” says Marcelo Martinez, UruIT Colombia Country Manager.

Technical Review 40

Technical Review Real Estate Airlines Strategic Planning 40

Progress

DECEMBER 30, 2019

Based on my interactions with thousands of developers in the Progress / Telerik developer tools ecosystem, I wrote a separate article contrasting Kinvey with Firebase. AWS Amplify is a good choice as a development platform when: Your team is proficient with building applications on AWS with DevOps, Cloud Services and Data Engineers.

AWS 10

AWS DevOps Disaster Recovery Serverless 10

Altexsoft

FEBRUARY 10, 2021

Unless you meet it in the article saying that “only 13 percent data science projects make it into production.” This sounds really ominous — especially, for companies heavily investing in data-driven transformations. New approaches arise to speed up the transformation of raw data into useful insights. DataOps vs DevOps.

Analytics 75

Analytics DevOps Development Software Review 75

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

O'Reilly Media - Ideas

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? The development phases for an AI project map nearly 1:1 to the AI Product Pipeline we described in the second article of this series. The final article in this series will be devoted to debugging.). Identifying the problem.

Marketing 145

Marketing Weak Development Team Metrics UI/UX 145

The Citus Data

MARCH 31, 2023

on-demand talk, performance, PostgreSQL) PostgreSQL Security: Defending Against External Attacks , by Taras Kloba, a big data engineering manager at SoftServe. (on-demand This article was originally published on citusdata.com.

Azure 85

Azure Open Source Virtualization Software Engineering 85

O'Reilly Media - Ideas

FEBRUARY 18, 2020

Also: infrastructure and operations is trending up, while DevOps is trending down. These trends are also implicated in the rise of infrastructure and ops, which reflects both the limitations of DevOps and the challenges posed by the shift to cloud native design. A drill-down into data, AI, and ML topics. Coincidence?

Technical Review 139

Technical Review Microservices Data Engineering Architecture 139

Altexsoft

MAY 27, 2020

But, in any case, the pipeline would provide data engineers with means of managing data for training, orchestrating models, and managing them on production. another jargon word, MLOps, which actually addresses the problem of DevOps in machine learning systems.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

Altexsoft

AUGUST 19, 2022

So, in this article, we’ll talk about the current BI market leader – Microsoft Power BI – and discuss its functionality, pros and cons, and alternatives. Microsoft Power BI is an interactive data visualization software suite developed by Microsoft that helps businesses aggregate, organize, and analyze data. What is Power BI?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Altexsoft

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Altexsoft

JULY 19, 2022

She formulated the thesis in 2018 and published her first article “How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” in 2019. Since that time, the data mesh concept has received a lot of attention and appreciation from companies pioneering this idea. What data mesh is NOT.

Architecture 52

Architecture Data Analytics Data Engineering 52

O'Reilly Media - Ideas

JANUARY 25, 2024

Rachel Stephens provides two fascinating pieces of the puzzle in a recent article on the RedMonk blog , but those pieces don’t fit together exactly. Data analysis and databases Data engineering was by far the most heavily used topic in this category; it showed a 3.6% SQL Server also showed a 5.3%

Trends 118

Trends Technical Review Technology Artificial Inteligence 118

Kentik

MAY 31, 2023

In this article, I want to underscore why NetOps has an integral role (and more responsibility) in delivering on the promise of reliability and highlight a few examples of how engineering for reliability can make networks less reliable. I wrote an article a while ago addressing latency.

Network 52

Network Cloud Load Balancer Firewall 52

Kentik

MARCH 7, 2023

Solving these problems for distributed cloud networks has required a big data approach, ultimately resulting in the evolution of network observability. Here are two scenarios from current and former clients managing data gravity and how network observability could have been used to triage or prevent the issue.

Network 99

Network Cloud Data Case Study 99

Altexsoft

SEPTEMBER 28, 2021

In this article, you will learn about its history, pros & cons, where it is applied, how it is faring against other popular languages, and how you can start learning it. web development, data analysis. machine learning , DevOps and system administration, automated-testing, software prototyping, and. What is Python?

Weak Development Team 94

Weak Development Team Programming Software Review Systems Review 94

Altexsoft

JANUARY 14, 2021

Though there are countless options for storing, analyzing, and indexing data, data warehouses have remained to the point. When reviewing BI tools , we described several data warehouse tools. In this article, we’ll take a closer look at the top cloud warehouse software, including Snowflake, BigQuery, and Redshift.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

DECEMBER 14, 2022

Taking this into account, Docker is a favorite of CI/CD practices and DevOps as it speeds up deployments, simplifies updates, and allows teammates to work efficiently together. Well-written documentation. Docker can boast its top-notch documentation. There are a few other open-source tools for building containers, but they rely on Docker.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

OCTOBER 24, 2019

And this data can be used to support decision making. While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. And this is what makes a data warehouse different from a Data Lake. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

AUGUST 22, 2022

Besides, the data fabric approach leaves the organization with a centralized team that is responsible for all the data, while data mesh implies distributed ownership of the data — each team has its own data products and they are responsible for its distribution to other teams. Data fabric vs data virtualization.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

O'Reilly Media - Ideas

MARCH 2, 2020

I read an article on the death of Agile. It’s not the first article I’ve seen claiming that Agile is dead, and I’m sure it won’t be the last. Also: infrastructure and operations is trending up, while DevOps is trending down. Key survey results: The C-suite is engaged with data quality. Coincidence?

Agile 21

Agile Artificial Inteligence Weak Development Team SCRUM 21

Altexsoft

DECEMBER 9, 2020

Moreover, the MicroStrategy Global Analytics Study reports that access to data is extremely limited, taking 60 percent of employees hours or even days to get the information they need. To generalize and describe the basic maturity path of an organization, in this article we will use the model based on the most common one suggested by Gartner.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

DECEMBER 15, 2021

The rest is done by data engineers, data scientists , machine learning engineers , and other high-trained (and high-paid) specialists. Also called DevOps for machine learning, MLOps is a mix of philosophy and practices that facilitates mutual understanding between a data science team and operations specialists.

Machine Learning 59

Machine Learning Artificial Inteligence How To Azure 59

Altexsoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. In this article, we’ll highlight the reasoning behind this choice and the challenges related to it. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JANUARY 25, 2021

Operations or DevOps or SRE. There’s been a lot of discussion about operations culture (the movement frequently known as DevOps), continuous integration and deployment (CI/CD), and site reliability engineering (SRE). The term “DevOps” has fallen on hard times. Operations, DevOps, and SRE.

Programming 145

Programming Cloud Artificial Inteligence Machine Learning 145