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

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

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

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.

Organization 158

Organization Artificial Intelligence Artificial Inteligence DevOps 158

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

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

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. A new capability called Ranger Authorization Service (RAZ) provides fine grained authorization on cloud storage.

Data Engineering 118

Data Engineering Technical Review Software Review Engineering 118

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

Cloudera

DECEMBER 2, 2024

As organizations adopt a cloud-first infrastructure strategy, they must weigh a number of factors to determine whether or not a workload belongs in the cloud. Cost has been a key consideration in public cloud adoption from the start. Meanwhile, GreenOps focuses on reducing the environmental impact of cloud operations.

Sustainability 89

Sustainability AWS Analytics Infrastructure 89

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. The same key tenants powering DE in the public clouds are now available in the data center.

Data Engineering 113

Data Engineering Engineering Data Storage 113

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. The cloud. The cloud is about more than managing costs. The cloud is an enabler for all that will come.

Leadership 218

Leadership IoT Machine Learning Artificial Inteligence 218

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

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. They are free to choose the infrastructure best suited for each workload.

Data 84

Data Analytics Systems Review Architecture 84

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 Machine Learning 98

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 62

Artificial Inteligence Open Source AWS Serverless 62

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. Within the data topic, however, ML+AI has gone from 22% of all usage to 26%.

Technical Review 145

Technical Review Microservices Data Engineering Architecture 145

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

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

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

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. These candidates should have experience debugging cloud stacks, securing apps in the cloud, and creating cloud-based solutions.

LAN 215

LAN Systems Administration How To Software Engineering 215

TechCrunch

JANUARY 26, 2022

Israeli startup Firebolt has been taking on Google’s BigQuery, Snowflake and others with a cloud data warehouse solution that it claims can run analytics on large datasets cheaper and faster than its competitors. Data warehouses are solving yesterday’s problem, which was, ‘How do I migrate to the cloud and deal with scale?’”

Analytics 218

Analytics Data Big Data Business Intelligence 218

CTOvision

MAY 1, 2014

A strong emphasis on data validation, testing, getting it right and knowing it stays right. Work collaboratively to deliver data in visually impactful ways. Take ownership of key components of the architecture powering Applied Intelligence analytics. Backend system automation. Qualifications.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

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. About the Authors Carole Suarez is a Senior Solutions Architect at AWS, where she helps guide startups through their cloud journey.

Generative AI 105

Generative AI CTO Coach AWS Artificial Inteligence 105

CIO

APRIL 27, 2023

For technologists with the right skills and expertise, the demand for talent remains and businesses continue to invest in technical skills such as data analytics, security, and cloud. The demand for specialized skills has boosted salaries in cybersecurity, data, engineering, development, and program management.

Technical Review 174

Technical Review Software Review Systems Review Software Engineering 174

CIO

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Organization 167

Organization Technical Review Data Artificial Inteligence 167

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. If your data isnt on the cloud yet, start that journey.

Meeting 52

Meeting Data Serverless Data Engineering 52

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

CIO

OCTOBER 20, 2023

It’s a vendor-specific certification that will benefit anyone who is tasked with working directly with AWS products and services or looking to make good on the high demand for cloud skills today. To earn your CompTIA A+ certification you’ll have to pass two separate exams.

SCRUM 206

SCRUM Azure AWS Agile 206

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

Cloudera

JUNE 14, 2021

How to optimize an enterprise data architecture with private cloud and multiple public cloud options? As the inexorable drive to cloud continues, telecommunications service providers (CSPs) around the world – often laggards in adopting disruptive technologies – are embracing virtualization.

Telecommunications 97

Telecommunications Cloud Data Virtualization 97

Abhishek Tiwari

FEBRUARY 26, 2020

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup.

Architecture 82

Architecture MVC Engineering Organization 82

CIO

APRIL 12, 2023

After walking his executive team through the data hops, flows, integrations, and processing across different ingestion software, databases, and analytical platforms, they were shocked by the complexity of their current data architecture and technology stack. It isn’t easy. Reducing complexity here is critical.

Artificial Inteligence 218

Artificial Inteligence Artificial Intelligence Machine Learning Agile 218

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 ). Deploying modern data architectures. Forrester ).

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

Cloudera

OCTOBER 5, 2020

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. This exciting initiative is built on our shared vision to make data-driven decision-making a reality for every business. “By with Spark 3.0

Enterprise 93

Enterprise Cloud Data Machine Learning 93

Xebia

MARCH 13, 2025

This is a common issue, especially when working in cloud environments. Features are computed in a feature engineering pipeline that writes features to the data store. Please have a look at this blog post on machine learning serving architectures if you do not know the difference. This drives computation costs.

Training 130

Training Machine Learning Artificial Inteligence Data 130