Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of. Usage Patterns.

Data Engineering 113

Data Engineering Engineering Data Storage 113

Cloudera

MAY 3, 2021

Cloudera sees success in terms of two very simple outputs or results – building enterprise agility and enterprise scalability. Contrast this with the skills honed over decades for gaining access, building data warehouses, performing ETL, creating reports and/or applications using structured query language (SQL). A rare breed.

Scalability 103

Scalability Agile Data Systems Review 103

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

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. CRM platforms).

Scalability 94

Scalability Data Technical Review Analytics 94

AWS Machine Learning - AI

MARCH 13, 2025

Amazon Bedrocks broad choice of FMs from leading AI companies, along with its scalability and security features, made it an ideal solution for MaestroQA. MaestroQA integrated Amazon Bedrock into their existing architecture using Amazon Elastic Container Service (Amazon ECS).

Generative AI 110

Generative AI CTO Coach AWS Artificial Inteligence 110

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 Machine Learning Artificial Inteligence 195

AWS Machine Learning - AI

APRIL 23, 2025

Designed with a serverless, cost-optimized architecture, the platform provisions SageMaker endpoints dynamically, providing efficient resource utilization while maintaining scalability. The following diagram illustrates the solution architecture. Key architectural decisions drive both performance and cost optimization.

Artificial Inteligence 66

Artificial Inteligence Open Source AWS Serverless 66

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

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 Machine Learning Artificial Inteligence SDLC 218

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

APRIL 22, 2025

.” What topics do you think will be top-of-mind for attendees this year? “Im especially interested in the intersection of data engineering and AI. Ive been lucky to work on modern data teams where weve adopted CI/CD pipelines and scalable architectures. It wont always be easybut it will be worth it.

Meeting 52

Meeting Data Serverless Data Engineering 52

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

AWS Machine Learning - AI

APRIL 1, 2025

With App Studio, technical professionals such as IT project managers, data engineers, enterprise architects, and solution architects can quickly develop applications tailored to their organizations needswithout requiring deep software development skills. Outside of work, Samit enjoys playing cricket, traveling, and biking.

AWS 93

AWS Software Review Technical Review Generative AI 93

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

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

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

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 Machine Learning 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

Capgemini

NOVEMBER 21, 2024

Snowflake and Capgemini powering data and AI at scale Capgemini October 13, 2020 Organizations slowed by legacy information architectures are modernizing their data and BI estates to achieve significant incremental value with relatively small capital investments. This evolution is also being driven by many industry factors.

Data 52

Data Government Innovation Architecture 52

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 How To Systems Administration 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.

Machine Learning 107

Machine Learning Artificial Inteligence 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 110

Data AWS Groups Knowledge Base 110

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

Mobilunity

AUGUST 3, 2021

Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer?

Big Data 52

Big Data Data Engineering Engineering Data 52

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 Machine Learning Artificial Inteligence 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

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 64

Compliance Systems Review Policies Storage 64

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 Development Security Programming 147