O'Reilly Media - Data

MAY 24, 2018

In particular, we examined the evolution of key topics covered in this podcast: data science and machine learning, data engineering and architecture, AI, and the impact of each of these areas on businesses and companies. Continue reading The evolution of data science, data engineering, and AI.

Data Engineering 180

Data Engineering Engineering Data Artificial Inteligence 180

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

CIO

NOVEMBER 19, 2024

The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows. The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both.

Artificial Inteligence 174

Artificial Inteligence Engineering Data Storage 174

CIO

MARCH 13, 2025

Hes seeing the need for professionals who can not only navigate the technology itself, but also manage increasing complexities around its surrounding architectures, data sets, infrastructure, applications, and overall security. We currently have about 10 AI engineers and next year, itll be around 30.

Part-Time VPE 205

Part-Time VPE Weak Development Team Fractional VPE Fractional CTO 205

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. The post Cloudera Data Engineering 2021 Year End Review appeared first on Cloudera Blog.

Data Engineering 118

Data Engineering Technical Review Software Review Engineering 118

CIO

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data 199

Data Data Engineering Database Administration Artificial Inteligence 199

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

CIO

JANUARY 3, 2025

Today, IT encompasses site reliability engineering (SRE), platform engineering, DevOps, and automation teams, and the need to manage services across multi-cloud and hybrid-cloud environments in addition to legacy systems. Experience and deliberate cross-functional learning opportunities are needed for people to acquire these skills.

Organization 158

Organization Artificial Intelligence Artificial Inteligence DevOps 158

CIO

DECEMBER 10, 2024

Choreographing data, AI, and enterprise workflows While vertical AI solves for the accuracy, speed, and cost-related challenges associated with large-scale GenAI implementation, it still does not solve for building an end-to-end workflow on its own. These models are then integrated into workflows along with human-in-the-loop guardrails.

Artificial Inteligence 174

Artificial Inteligence Off-The-Shelf Insurance Analytics 174

Xebia

APRIL 9, 2025

For example, events such as Twitters rebranding to X, and PySparks rise in the data engineering realm over Spark have all contributed to this decline. The initial excitement that once propelled the language into the limelight during the mid-2010s has diminished over the last 15 years.

Systems Review 130

Systems Review Programming Technical Review Engineering 130

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

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

Dzone - DevOps

OCTOBER 30, 2023

To tackle this challenge head-on, software-based architectures are emerging as powerful solutions. 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.

IoT 95

IoT Architecture Software Data Engineering 95

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

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Introduction to the Data Mesh Architecture and its Required Capabilities.

Architecture 124

Architecture Data Security Technical Review 124

CIO

NOVEMBER 7, 2024

It covers essential topics like artificial intelligence, our use of data models, our approach to technical debt, and the modernization of legacy systems. We explore the essence of data and the intricacies of data engineering. I think we’re very much on our way.

Artificial Inteligence 180

Artificial Inteligence Development Generative AI Artificial Intelligence 180

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions.

Data Engineering 108

Data Engineering Engineering Data Systems Review 108

Cloudera

DECEMBER 2, 2024

Cloudera is committed to providing the most optimal architecture for data processing, advanced analytics, and AI while advancing our customers’ cloud journeys. Today, Cloudera Data Engineering, a data service that streamlines and scales data pipeline development, is available with support for AWS Graviton processors.

Sustainability 89

Sustainability AWS Analytics Infrastructure 89

CIO

APRIL 1, 2025

Job titles like data engineer, machine learning engineer, and AI product manager have supplanted traditional software developers near the top of the heap as companies rush to adopt AI and cybersecurity professionals remain in high demand.

Marketing 152

Marketing Software Development Software Development 152

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

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Engineering 95

Data Engineering Engineering Data Cloud 95

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 SDLC Artificial Inteligence 218

TechCrunch

FEBRUARY 2, 2022

But, as RudderStack CEO Soumyadeb Mitra argued when I talked to him ahead of today’s announcement, most of the existing customer data pipeline solutions were built for selling to marketing teams, using architectures that make it harder to build the advanced applications that businesses are now looking for.

Data 204

Data Artificial Inteligence Machine Learning Architecture 204

Cloudera

APRIL 14, 2021

What is Cloudera Data Engineering (CDE) ? Cloudera Data Engineering is a serverless service for Cloudera Data Platform (CDP) that allows you to submit jobs to auto-scaling virtual clusters. Refer to the following cloudera blog to understand the full potential of Cloudera Data Engineering. .

Data Engineering 84

Data Engineering Engineering Data Serverless 84

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Data 84

Data Analytics Systems Review Architecture 84

CIO

JANUARY 22, 2025

Were going to identify and hire data engineers and data scientists from within and beyond our organization and were going to get ahead, he says. Outdated systems, overly customized applications, and fragmented architectures slow progress, increase risks, and make scaling innovations harder.

Weak Development Team 192

Weak Development Team Education Meeting Data 192

Perficient

MARCH 13, 2025

In this case, Liquid Clustering addresses the data management and query optimization aspects of cost control soi simply and elegantly that I’m happy to take my hands off the controls. This made intuitive sense to me as an early Spark developer, and I had deep knowledge of both architectures.

Data Engineering 64

Data Engineering Government Engineering Data 64

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

O'Reilly Media - Ideas

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Trends in software architecture, infrastructure, and operations.

Technical Review 145

Technical Review Microservices Data Engineering Architecture 145

Cloudera

DECEMBER 4, 2024

introduces new features specifically designed to fuel GenAI initiatives: New AI Processors: Harness the power of cutting-edge AI models with new processors that simplify integration and streamline data preparation for GenAI applications. Accelerating GenAI with Powerful New Capabilities Cloudera DataFlow 2.9

Metrics 93

Metrics Generative AI Open Source Data Engineering 93

AWS Machine Learning - AI

MARCH 13, 2025

MaestroQA integrated Amazon Bedrock into their existing architecture using Amazon Elastic Container Service (Amazon ECS). The following architecture diagram demonstrates the request flow for AskAI. The customer interaction transcripts are stored in an Amazon Simple Storage Service (Amazon S3) bucket.

Generative AI 113

Generative AI CTO Coach AWS Artificial Inteligence 113

AWS Machine Learning - AI

NOVEMBER 15, 2024

Some users lacked access to corporate data, but they used the platform as a generative AI chatbot to securely attach internal-use documentation (also called initial generic entitlement) and query it in real time or to ask questions of the model’s foundational knowledge without risk of data leaving the tenant.

Generative AI 113

Generative AI AWS Groups Artificial Inteligence 113

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 Machine Learning Artificial Inteligence 64

Confluent

JUNE 18, 2019

As soon as the number of data points involved in your search feature increases, typically we’ll introduce a broker in between all the involved components. This architectural pattern provides several benefits: Better scalability by allowing multiple data producers and consumers to run in parallel.

Scalability 97

Scalability Architecture Artificial Inteligence Machine Learning 97

CIO

SEPTEMBER 19, 2024

The challenge is that these architectures are convoluted, requiring multiple models, advanced RAG [retrieval augmented generation] stacks, advanced data architectures, and specialized expertise.” Reinventing the wheel is indeed a bad idea when it comes to complex systems like agentic AI architectures,” he says.

CTO Coach 207

CTO Coach Artificial Inteligence Open Source Fractional CTO 207

Perficient

FEBRUARY 13, 2023

Introduction: We often end up creating a problem while working on data. So, here are few best practices for data engineering using snowflake: 1.Transform Each data model has its own advantages and storing intermediate step results has significant architectural advantages.

Data Engineering 69

Data Engineering Engineering Data Storage 69