CIO

AUGUST 3, 2022

The target architecture of the data economy is platform-based , cloud-enabled, uses APIs to connect to an external ecosystem, and breaks down monolithic applications into microservices. To solve this, we’ve kept data engineering in IT, but embedded machine learning experts in the business functions. The cloud.

Leadership 218

Leadership IoT Artificial Inteligence Machine Learning 218

CIO

FEBRUARY 14, 2023

Cloud-native apps, microservices and mobile apps drive revenue with their real-time customer interactions. It’s clear how these real-time data sources generate data streams that need new data and ML models for accurate decisions. It’s also used to deploy machine learning models, data streaming platforms, and databases.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

CIO

SEPTEMBER 2, 2022

You’ll be required to write code, troubleshoot systems, fix bugs, and assist with the development of microservices. In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

You’ll be required to write code, troubleshoot systems, fix bugs, and assist with the development of microservices. In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

Dzone - DevOps

SEPTEMBER 6, 2024

Considering data engineering and data science, Astro and Apache Airflow rise to the top as important tools used in the management of these data workflows. This should help software developers and data engineers in selecting the right tool for their specific needs and project requirements.

Comparison 91

Comparison Microservices Data Engineering Software Development 91

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 145

Weak Development Team Data Technical Review Survey 145

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 82

Architecture MVC Engineering Organization 82

Kentik

NOVEMBER 16, 2015

KDE handles over 10B flow records/day with a microservice architecture that's optimized using metrics. Here at Kentik, our Kentik Detect service is powered by a multi-tenant big data datastore called Kentik Data Engine. So it was critical to instrument every component leading to, around, and within our data engine.

Metrics 40

Metrics Microservices Linux Architecture 40

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 98

Conference Artificial Inteligence UI/UX Machine Learning 98

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

O'Reilly Media - Ideas

JUNE 4, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Microservices Architecture and Design , July 8-9. Practical Linux Command Line for Data Engineers and Analysts , July 22. Domain-driven design and event-driven microservices , July 23-24.

Course 92

Course Training Artificial Inteligence Software Review 92

Cloudera

MAY 8, 2023

Out of the box Cloudera Data platform (CDP) performs superbly but over time, if data architecture, data engineering, and DevOps best practices are not maintained, you can get stuck maintaining the wild, wild west. In this six-part series, we’re focused on improving the health of your environment.

Data Engineering 77

Data Engineering Microservices DevOps Engineering 77

Netflix Tech

FEBRUARY 14, 2025

Stay tuned for the next part of this series, where well delve into how we use this SOT dataset to create a microservice that provides impression histories. Conclusion Creating a reliable source of truth for impressions is a complex but essential task that enhances personalization and discovery experience.

Systems Review 66

Systems Review Technical Review Data Metrics 66

O'Reilly Media - Ideas

MARCH 6, 2019

Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. Foundational Data Science with R , March 26-27. What You Need to Know About Data Science , April 1. Microservice Fundamentals , April 15.

Course 15

Course Artificial Inteligence Training Machine Learning 15

Apiumhub

NOVEMBER 17, 2022

Russ Miles – Chaos Engineer Thought Leader & Author of multiple books including “Antifragile Software: Building Adaptable Software with Microservices”. Chris Richardson – Developer & Architect, Author of “POJOs in Action“ and “Microservices patterns“, Founder at Eventuate.

Technical Review 81

Technical Review Software Review Fractional CTO CTO Coach 81

O'Reilly Media - Ideas

MARCH 1, 2022

And Holochain is a decentralized framework for building peer-to-peer microservices–no cloud provider needed. ApacheHop is a metadata-driven data orchestration for building dataflows and data pipelines. It integrates with Spark and other data engines, and is programmed using a visual drag-and-drop interface, so it’s low code.

Trends 116

Trends Blockchain Serverless Malware 116

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

Apiumhub

APRIL 18, 2019

We can’t wait to attend them all: Best practices in a modern (microservices) environment by Alvaro García. Micro Frontend: the microservice puzzle extended to frontend by Audrey Neveu. Nowadays Architecture Trends, from Monolith to Microservices and Serverless by Alberto Salazar. Responsible Microservices by Nate Schutta.

Technical Review 57

Technical Review Microservices Software Review CTO Coach 57

O'Reilly Media - Ideas

JUNE 5, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. Microservices Architecture and Design , July 8-9. Practical Linux Command Line for Data Engineers and Analysts , July 22. Domain-driven design and event-driven microservices , July 23-24.

Course 69

Course Training Artificial Inteligence Software Review 69

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Native frameworks.

Big Data 63

Big Data Data Storage Microservices 63

Cloudera

OCTOBER 7, 2021

The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e.,

Architecture 124

Architecture Data Security Technical Review 124

O'Reilly Media - Ideas

MARCH 18, 2020

One-sixth of respondents identify as data scientists, but executives—i.e., The survey does have a data-laden tilt, however: almost 30% of respondents identify as data scientists, data engineers, AIOps engineers, or as people who manage them. All told, more than 70% of respondents work in technology roles.

Enterprise 139

Enterprise Survey Technical Review Weak Development Team 139

Abhishek Tiwari

JULY 12, 2018

In this post, we will discuss why you should avoid building data pipelines in first place. Depending on the use cases, it is quite possible that you can achieve similar outcomes by using techniques such as data virtualisation or simply building microservices. It can be used to power new analytics, insight, and product features.

Data 63

Data Software Review Technical Review Microservices 63

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. Microservices Caching Strategies , June 17.

Course 62

Course Training Artificial Inteligence Machine Learning 62

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. You have existing backend services developed on AWS.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

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. You have existing backend services developed on AWS.

AWS 52

AWS DevOps Disaster Recovery Serverless 52

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. You have existing backend services developed on AWS.

AWS 10

AWS DevOps Disaster Recovery Serverless 10

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

Cloudera

OCTOBER 14, 2020

A single, unified infrastructure for both majority of batch workloads and microservices. Cloudera’s CDP platform offers Cloudera Data Engineering experience which is powered by Apache YuniKorn (Incubating). Fine-grained access controls on shared clusters. Apache YuniKorn (Incubating) in CDP.

Policies 118

Policies Resources Systems Review Technical Review 118

Kentik

FEBRUARY 7, 2023

This might mean a complete transition to cloud-based services and infrastructure or isolating an IT or business domain in a microservice, like data backups or auth, and establishing proof-of-concept. Either way, it’s a step that forces teams to deal with new data, network problems, and potential latency.

Network 59

Network Cloud Data Data Center 59

Netflix Tech

MARCH 7, 2024

Since then, open-source Metaflow has gained support for Argo Workflows , a Kubernetes-native orchestrator, as well as support for Airflow which is still widely used by data engineering teams. Internally, we use a production workflow orchestrator called Maestro. Metaflow Hosting caches the response, so Amber can fetch it after a while.

System 94

System Machine Learning Artificial Inteligence Open Source 94

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Abhishek Tiwari

DECEMBER 27, 2017

Data solution vendors like SnapLogic and Informatica are already developing machine learning and artificial intelligence (AI) based smart data integration assistants. These assistants can recommend next-best-action or suggest datasets, transforms, and rules to a data engineer working on a data integration project.

Trends 49

Trends Artificial Inteligence Data Big Data 49

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 Machine Learning Data Center 86

Confluent

FEBRUARY 22, 2019

Our quickly expanding business also means our platform needs to keep ahead of the curve to accommodate the ever-growing volumes of data and increasing complexity of our systems. The Deliveroo Engineering organisation is in the process of decomposing a monolith application into a suite of microservices.

Data 81

Data Software Review Weak Development Team Systems Review 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

Cloudera

APRIL 26, 2023

It offers features such as data ingestion, storage, ETL, BI and analytics, observability, and AI model development and deployment. The platform offers advanced capabilities for data warehousing (DW), data engineering (DE), and machine learning (ML), with built-in data protection, security, and governance.

Cloud 64

Cloud Data Load Balancer Storage 64