CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 324

Analytics Data Engineering Machine Learning Artificial Inteligence 324

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Mentormate

JANUARY 11, 2022

Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration. That lack of support leaves the citizen report builders and data scientists with no way to act on that data.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

O'Reilly Media - Ideas

JULY 15, 2020

Microservices seem to be everywhere. Scratch that: talk about microservices seems to be everywhere. So we wanted to determine to what extent, and how, O’Reilly subscribers are empirically using microservices. Here’s a summary of our key findings: Most adopters are successful with microservices. And that’s the problem.

Microservices 138

Microservices Weak Development Team Survey Architecture 138

d2iq

FEBRUARY 19, 2021

Components that are unique to data engineering and machine learning (red) surround the model, with more common elements (gray) in support of the entire infrastructure on the periphery. Before you can build a model, you need to ingest and verify data, after which you can extract features that power the model.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Progress

DECEMBER 30, 2019

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. You’re developing a greenfield application that doesn’t require any external data or auth systems.

AWS 10

AWS DevOps Disaster Recovery Serverless 10

O'Reilly Media - Ideas

MAY 1, 2019

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. Data Visualization with Matplotlib and Seaborn , June 4. Network DevOps , June 6.

Course 46

Course Training Artificial Inteligence Machine Learning 46

O'Reilly Media - Ideas

FEBRUARY 18, 2020

Also: infrastructure and operations is trending up, while DevOps is trending down. It’s possible that microservices architecture is hastening the move to other languages (such as Go, Rust, and Python) for web properties. This also helps explain increased usage in the microservices topic, which grew at a 22% clip in 2019.

Technical Review 136

Technical Review Microservices Data Engineering Architecture 136

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. How DataOps relates to Agile, DevOps, and MLOps.

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. Happy New Year and welcome to 2019, a year full of possibilities.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

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. To enable the model reading this data, we need to process it, and transform into features that a model can consume. Generating predictions.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Microservices saw a 20% drop. Many developers expressed frustration with microservices during the year and argued for a return to monoliths.

Trends 114

Trends Technical Review Technology Artificial Inteligence 114

Abhishek Tiwari

FEBRUARY 26, 2020

Skills++: Induct specialised Frontend, Backend & QA engineers, Technical Leadership 21-30 Engineers Focus: Building quality in products and continue to innovate while proactively planning team structure, incentives, and culture. Architecture: Small microservices targeting new features. Adopt DevSecOps best-practices.

Architecture 81

Architecture MVC Engineering Technology 81

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 124

Weak Development Team Data Technical Review Survey 124

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 102

Continuous Delivery Google Cloud Data Engineering Microservices 102

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

BPM

JANUARY 18, 2019

The microservice movement will reignite the need for orchestration. Some analyst is bound to rename BPM engines to Microservice Orchestration Engines (MOE).wait Customer demand for solutions built on lean, loosely coupled BPM microservices will skyrocket. wait did I just do that. Lloyd Dugan BPM.com [link].

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

DECEMBER 14, 2022

delivering microservice-based and cloud-native applications; standardized continuous integration and delivery ( CI/CD ) processes for applications; isolation of multiple parallel applications on a host system; faster application development; software migration; and. Common Docker use cases. Typical areas of application of Docker are.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 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

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” That’s no longer true. Programming Languages.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

O'Reilly Media - Ideas

JANUARY 25, 2021

We’ll be working with microservices and serverless/functions-as-a-service in the cloud for a long time–and these are inherently concurrent systems. Operations or DevOps or SRE. The term “DevOps” has fallen on hard times. Operations, DevOps, and SRE. We can’t just get faster processors.

Programming 145

Programming Cloud Artificial Inteligence Machine Learning 145