Netflix Tech

JUNE 20, 2024

A summary of sessions at the first Data Engineering Open Forum at Netflix on April 18th, 2024 The Data Engineering Open Forum at Netflix on April 18th, 2024. At Netflix, we aspire to entertain the world, and our data engineering teams play a crucial role in this mission by enabling data-driven decision-making at scale.

Data Engineering 82

Data Engineering Engineering Data Generative AI 82

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 195

Analytics Data Engineering Artificial Inteligence Machine Learning 195

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 102

Architecture Innovation Data Open Source 102

AWS Machine Learning - AI

NOVEMBER 15, 2024

The Principal AI Enablement team, which was building the generative AI experience, consulted with governance and security teams to make sure security and data privacy standards were met. The following diagram illustrates the Principal generative AI chatbot architecture with AWS services.

Generative AI 113

Generative AI AWS Groups Artificial Inteligence 113

CTOvision

MAY 1, 2014

The senior engineer will have a great deal of freedom in choosing the right tools for the job, and will have strong support in getting it right. A strong emphasis on data validation, testing, getting it right and knowing it stays right. Work collaboratively to deliver data in visually impactful ways. Primary Responsibilities.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

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

Perficient

FEBRUARY 13, 2025

Breaking down silos has been a drumbeat of data professionals since Hadoop, but this SAP <-> Databricks initiative may help to solve one of the more intractable data engineering problems out there. SAP has a large, critical data footprint in many large enterprises. However, SAP has an opaque data model.

Government 64

Government Open Source Artificial Inteligence Machine Learning 64

CIO

JUNE 19, 2024

Platform engineering: purpose and popularity Platform engineering teams are responsible for creating and running self-service platforms for internal software developers to use. They may also ensure consistency in terms of processes, architecture, security, and technical governance.

Weak Development Team 208

Weak Development Team Engineering UI/UX Software Development 208

CIO

APRIL 27, 2023

The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management. Solutions architect Solutions architects are responsible for building, developing, and implementing systems architecture within an organization, ensuring that they meet business or customer needs.

Technical Review 174

Technical Review Software Review Systems Review Software Engineering 174

TechCrunch

JANUARY 26, 2022

However, over time, as the data produced in organizations continues to expand and grow ever more complex, it has put a huge strain on organizations, both in terms of the costs of managing that data, and the investment needed to parse it in useful ways.

Analytics 218

Analytics Data Big Data Business Intelligence 218

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 article compares Astro and Apache Airflow, explaining their architecture, features, scalability, usability, community support, and integration capabilities.

Comparison 91

Comparison Microservices Data Engineering Software Development 91

Apiumhub

JANUARY 26, 2022

Data engineer roles have gained significant popularity in recent years. Number of studies show that the number of data engineering job listings has increased by 50% over the year. And data science provides us with methods to make use of this data. Who are data engineers?

Data Engineering 52

Data Engineering Engineering Data Artificial Inteligence 52

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Solutions that support MDAs are purpose-built for data collection, processing, and sharing.

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

CIO

JANUARY 6, 2023

But 86% of technology managers also said that it’s challenging to find skilled professionals in software and applications development, technology process automation, and cloud architecture and operations. Companies will have to be more competitive than ever to land the right talent in these high-demand areas.

LAN 215

LAN Systems Administration How To Software Engineering 215

CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. Many companies today struggle with legacy software applications and complex environments, which leads to difficulty in integrating new data elements or services.

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

AWS Machine Learning - AI

NOVEMBER 20, 2024

Amazon S3 is an object storage service that offers industry-leading scalability, data availability, security, and performance. This custom knowledge base that connects these diverse data sources enables Amazon Q to seamlessly respond to a wide range of sales-related questions using the chat interface. Akchhaya Sharma is a Sr.

Data 111

Data AWS Groups Knowledge Base 111

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. Data warehouse architecture.

Backup 115

Backup Azure Software Review Architecture 115

CIO

OCTOBER 18, 2023

To do so, the team had to overcome three major challenges: scalability, quality and proactive monitoring, and accuracy. The project, dubbed Real-Time Prediction of Intradialytic Hypotension Using Machine Learning and Cloud Computing Infrastructure, has earned Fresenius Medical Care a 2023 CIO 100 Award in IT Excellence.

Artificial Inteligence 200

Artificial Inteligence Analytics Machine Learning Artificial Intelligence 200

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

Perficient

MARCH 23, 2023

Databricks Streaming and Apache Flink are two popular stream processing frameworks that enable developers to build real-time data pipelines, applications and services at scale. Comparison Databricks is an integrated platform for data engineering, machine learning, data science and analytics built on top of Apache Spark.

Data 83

Data Artificial Inteligence Machine Learning Data Engineering 83

Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

Kentik

OCTOBER 25, 2016

How Scalable Architecture Boosts Accuracy in Detection. The out-of-band architecture also provides the option to utilize hybrid mitigation techniques that are tailored to specific needs and objectives. These issues are rooted in the inherent compute and storage limitations of scale-up detection architectures.

Scalability 40

Scalability Architecture Big Data Network 40

CIO

SEPTEMBER 2, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

JULY 29, 2022

For example, if a data team member wants to increase their skills or move to a data engineer position, they can embark on a curriculum for up to two years to gain the right skills and experience. The bootcamp broadened my understanding of key concepts in data engineering.

Groups 147

Groups Security Development Programming 147

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. Give us a holler if you are interested in a thought exchange.

Infrastructure 74

Infrastructure Scalability Cloud Data 74

Perficient

MARCH 27, 2025

Our Databricks Practice holds FinOps as a core architectural tenet, but sometimes compliance overrules cost savings. Ensuring compliant data deletion is a critical challenge for data engineering teams, especially in industries like healthcare, finance, and government. What Are Deletion Vectors?

Compliance 52

Compliance Systems Review Policies Storage 52

AWS Machine Learning - AI

MARCH 13, 2025

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

Artificial Inteligence 101

Artificial Inteligence Systems Review System Generative AI 101

CIO

SEPTEMBER 18, 2023

IDC analyst Jason Leigh says Verizon made the right move to build a tool to facilitate customer migrations, but adds that there will be challenges whenever a CIO or C-suite move their data and traffic to new environments.

Telecommunications 167

Telecommunications Network Systems Review Software Review 167

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Agile Engine

DECEMBER 2, 2019

AgileEngine is a collective of 400+ software developers, QAs, designers, data engineers, and managers working with 50+ companies on more than 70 digital products. We’ve also enabled our clients to reengineer old-school monoliths into modern scalable architectures that leverage technologies like Node, Scala, and services like AWS.

Software 19

Software Company Blockchain Software Development 19

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data 101

Data Storage Architecture Big Data 101

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Data 110

Data Analytics Disaster Recovery Travel 110

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). But the current data lakehouse architectural pattern is not enough.

Data 88

Data Analytics Artificial Inteligence Machine Learning 88

Mentormate

JANUARY 11, 2022

Only the largest engineering organizations have the scale to make this kind of continuous investment. Human-Centered Design, Composable Architectures, and Citizen Builders. Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52