Dzone - DevOps

DECEMBER 31, 2024

MLOps, or Machine Learning Operations, is a set of practices that combine machine learning (ML), data engineering, and DevOps to streamline and automate the end-to-end ML model lifecycle. MLOps is an essential aspect of the current data science workflows.

Machine Learning 96

Machine Learning Artificial Inteligence Scalability Data Engineering 96

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

Xebia

DECEMBER 23, 2024

Scalability and Flexibility: The Double-Edged Sword of Pay-As-You-Go Models Pay-as-you-go pricing models are a game-changer for businesses. In these scenarios, the very scalability that makes pay-as-you-go models attractive can undermine an organization’s return on investment.

Data 130

Data Storage Culture Resources 130

CIO

MARCH 13, 2025

In this role, he strategically partners with business leaders, analytics leaders, data scientists, data analysts, data engineers and technology teammates to provide solutions that address real business challenges and opportunities in a meaningful and scalable way and is a champion for the creation of a data-driven and innovation-focused culture to (..)

Company 186

Company Generative AI Insurance Education 186

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 83

Data Engineering Engineering Data Generative AI 83

TechCrunch

FEBRUARY 7, 2022

Advances in cloud-based location service are ushering in a new era of location intelligence by helping data engineers, analysts, and developers integrate location data into their existing infrastructure, build data pipelines, and reap insights more efficiently.

Business Intelligence 230

Business Intelligence AWS Data Engineering Sustainability 230

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

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. For this reason and others as well, many projects start using their database for everything, and over time they might move to a search engine like Elasticsearch or Solr. You might be wondering, is this a good solution?

Scalability 97

Scalability Architecture Machine Learning Artificial Inteligence 97

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

TechCrunch

MARCH 7, 2023

But the AI core team should include at least three personas, all of which will be equally important for the success of the project: data scientist, data engineer and domain expert. Like all automation efforts, it’s good to start by showing the value of a few examples in a manual, slow and non-scalable manner.

Weak Development Team 246

Weak Development Team Case Study Data Engineering ChatGPT 246

Cloudera

SEPTEMBER 2, 2021

At Cloudera, we introduced Cloudera Data Engineering (CDE) as part of our Enterprise Data Cloud product — Cloudera Data Platform (CDP) — to meet these challenges. The post Optimizing Cloudera Data Engineering Autoscaling Performance appeared first on Cloudera Blog. fixed sized clusters).

Data Engineering 85

Data Engineering Performance Engineering Data 85

CIO

FEBRUARY 25, 2025

In this role, he strategically partners with business leaders, analytics leaders, data scientists, data analysts, data engineers and technology teammates to provide solutions that address real business challenges and opportunities in a meaningful and scalable way and is a champion for the creation of a data-driven and innovation-focused culture to (..)

Data 136

Data Innovation Insurance Culture 136

TechCrunch

APRIL 26, 2021

“We are, I believe, a really effective and scalable AI company, not just for the U.K. Palantir doesn’t really do AI, they do data engineering in a big way. I asked him why Faculty had attracted VC when, typically, VCs invest in startups that have scalable products. but we’re working in the U.S.

Artificial Inteligence 231

Artificial Inteligence Machine Learning Artificial Intelligence Scalability 231

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. Primary Responsibilities. Projects will involve designing and building a new system in the following areas: Analytics Infrastructure: Hadoop, HDFS, HBase or Cassandra, Pig or Hive.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

TechCrunch

NOVEMBER 4, 2022

I know this because I used to be a data engineer and built extract-transform-load (ETL) data pipelines for this type of offer optimization. Part of my job involved unpacking encrypted data feeds, removing rows or columns that had missing data, and mapping the fields to our internal data models.

Data 218

Data Storage Analytics Data Engineering 218

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

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

TechCrunch

NOVEMBER 2, 2022

For advanced users and data teams, Y42 offers Git-based version control (though non-technical users can leverage this through the service’s web app, too) and with this new platform, the company also now offers enhanced governance tools like a data catalog, asset ownership assignments, data contracts and multi-level access controls.

Data 203

Data Business Intelligence Open Source Government 203

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. Carole specializes in data engineering and holds an array of AWS certifications on a variety of topics including analytics, AI, and security.

Generative AI 113

Generative AI CTO Coach AWS Artificial Inteligence 113

Xebia

NOVEMBER 21, 2024

But when the size of a dbt project grows, and the number of developers increases, then an automated approach is often the only scalable way forward. Our analytics engineer consultants are here to help – just contact us and we’ll get back to you soon.

Weak Development Team 130

Weak Development Team Testing Analytics Engineering 130

CIO

APRIL 10, 2024

As with many data-hungry workloads, the instinct is to offload LLM applications into a public cloud, whose strengths include speedy time-to-market and scalability. Inferencing funneled through RAG must be efficient, scalable, and optimized to make GenAI applications useful. Inferencing and… Sherlock Holmes???

Artificial Inteligence 203

Artificial Inteligence Generative AI Storage Artificial Intelligence 203

CIO

OCTOBER 9, 2024

The data preparation process should take place alongside a long-term strategy built around GenAI use cases, such as content creation, digital assistants, and code generation. Known as data engineering, this involves setting up a data lake or lakehouse, with their data integrated with GenAI models.

Strategy 215

Strategy Data Artificial Inteligence Storage 215

Apiumhub

DECEMBER 9, 2024

Integrated Data Lake Synapse Analytics is closely integrated with Azure Data Lake Storage (ADLS), which provides a scalable storage layer for raw and structured data, enabling both batch and interactive analytics. When Should You Use Azure Synapse Analytics?

Azure 91

Azure Analytics Storage Machine Learning 91

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 103

AWS Software Review Technical Review Generative AI 103

Dataiku

JUNE 15, 2022

One key to more efficient, effective AI model and application development is executing workloads on compute platforms that offer high scalability, performance, and concurrency.

Data Engineering 59

Data Engineering Engineering Data Development 59

Netflix Tech

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Dhevi Rajendran Dhevi Rajendran This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Data Engineers of Netflix?—?Interview

Data Engineering 56

Data Engineering Engineering Data Culture 56

CIO

AUGUST 3, 2022

It is a mindset that lets us zoom in to think vertically about how we deliver to the farmer, vet, and pet owner, and then zoom out to think horizontally about how to make the solutions reusable, scalable, and secure. To solve this, we’ve kept data engineering in IT, but embedded machine learning experts in the business functions.

Leadership 218

Leadership SDLC IoT Machine Learning 218

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

TechCrunch

FEBRUARY 23, 2022

Portland, Oregon-based startup thatDot , which focuses on streaming event processing, today announced the launch of Quine , a new MIT-licensed open source project for data engineers that combines event streaming with graph data to create what the company calls a “streaming graph.”

Engineering 190

Engineering Open Source Big Data Fintech 190

TechCrunch

JULY 25, 2022

The company was founded in 2021 by Brian Ip, a former Goldman Sachs executive, and data engineer YC Chan. He added that this disadvantage of payroll software is that they only provide basic admin functions around payroll calculation, and are not scalable.

Recruiting 224

Recruiting Technical Review Software Review Systems Review 224

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

John Snow Labs

SEPTEMBER 26, 2024

This makes it hard to combine them together, especially with growing data volumes. Unfortunately, unharmonized data is not fit for use in customer analytics, risk and compliance and data engineers and scientists end up building some sort of rule or heuristic based system to manage it.

Scalability 52

Scalability Open Source Data Engineering Compliance 52

CIO

OCTOBER 1, 2022

Cretella says P&G will make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations, and manufacturing sustainability optimization. These things have not been done at this scale in the manufacturing space to date, he says.

Artificial Inteligence 218

Artificial Inteligence Azure IoT Analytics 218

TechCrunch

FEBRUARY 10, 2021

Tomo Credit feels to me like it is tackling this in a hugely scalable, mainstream way.”. Looking ahead, Tomo plans to use its new capital to triple its headcount of 15, mostly with the goal of hiring full stack and data engineers.

Weak Development Team 253

Weak Development Team Banking Fintech Data Engineering 253

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. Serverless on AWS AWS GovCloud (US) Generative AI on AWS About the Authors Nick Biso is a Machine Learning Engineer at AWS Professional Services.

Artificial Inteligence 67

Artificial Inteligence Open Source AWS Serverless 67

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. All AWS services are high-performing, secure, scalable, and purpose-built. Joel Elscott is a Senior Data Engineer on the Principal AI Enablement team.

Generative AI 113

Generative AI AWS Groups Artificial Inteligence 113