Xebia

DECEMBER 23, 2024

A lack of monitoring might result in idle clusters running longer than necessary, overly broad data queries consuming excessive compute resources, or unexpected storage costs due to unoptimized data retention. Once the decision is made, inefficiencies can be categorized into two primary areas: compute and storage.

Data 130

Data Storage Culture Resources 130

Toptal

DECEMBER 6, 2016

With the rise of big data and data science, storage and retrieval have become a critical pipeline component for data use and analysis. Recently, new data storage technologies have emerged. Which one is best suited for data engineering? But the question is: Which one should you choose?

Data Engineering 85

Data Engineering Storage Engineering Data 85

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. Securing and scaling storage. Test Drive CDP Pubic Cloud.

Data Engineering 118

Data Engineering Technical Review Software Review Engineering 118

Cloudera

DECEMBER 2, 2024

Lakehouse Optimizer : Cloudera introduced a service that automatically optimizes Iceberg tables for high-performance queries and reduced storage utilization. The net result is that queries are more efficient and run for shorter durations, while storage costs and energy consumption are reduced. Give it a try today.

Sustainability 89

Sustainability AWS Analytics Infrastructure 89

O'Reilly Media - Ideas

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Data engineering is not in the limelight.

Data Engineering 112

Data Engineering Engineering Data Technical Review 112

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

Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

Data Engineering 104

Data Engineering Engineering Data Tools 104

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

The Crazy Programmer

NOVEMBER 6, 2021

A cloud architect has a profound understanding of storage, servers, analytics, and many more. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. And as a big data engineer, you need to work around the big data sets of the applications.

Artificial Inteligence 290

Artificial Inteligence Blockchain Software Review Artificial Intelligence 290

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

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

Apiumhub

DECEMBER 9, 2024

Azure Key Vault Secrets offers a centralized and secure storage alternative for API keys, passwords, certificates, and other sensitive statistics. Azure Key Vault is a cloud service that provides secure storage and access to confidential information such as passwords, API keys, and connection strings. What is Azure Key Vault Secret?

Azure 89

Azure Analytics Storage Artificial Inteligence 89

CIO

OCTOBER 13, 2023

Big data architect: The big data architect designs and implements data architectures supporting the storage, processing, and analysis of large volumes of data. Data architect vs. data engineer The data architect and data engineer roles are closely related.

Data 199

Data Database Administration Data Engineering Artificial Inteligence 199

Netflix Tech

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer at Netflix.

Data Engineering 72

Data Engineering Engineering Data Software Engineering 72

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. This greatly increases data processing capabilities.

Big Data 75

Big Data Data Engineering Engineering Data 75

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

Netflix Tech

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 84

Storage Data Resources Data Engineering 84

Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. That is why cloud native solutions which take advantage of the capabilities such as disaggregated storage & compute, elasticity, and containerization are more paramount than ever.

Data Engineering 85

Data Engineering Performance Engineering Data 85

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. Data-obsessed individuals such as Sherlock Holmes knew full well the importance of inferencing in making predictions, or in his case, solving mysteries.

Artificial Inteligence 203

Artificial Inteligence Generative AI Storage Artificial Intelligence 203

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 So, resist the temptation to periodically load data using other methods (such as querying external tables). Use it, but don’t use it for normal large data loads.

Data Engineering 69

Data Engineering Engineering Data Storage 69

Cloudera

SEPTEMBER 10, 2021

Shared Data Experience ( SDX ) on Cloudera Data Platform ( CDP ) enables centralized data access control and audit for workloads in the Enterprise Data Cloud. The public cloud (CDP-PC) editions default to using cloud storage (S3 for AWS, ADLS-gen2 for Azure).

Storage 83

Storage Cloud Azure Pharmaceuticals 83

Cloudera

OCTOBER 23, 2024

The Iceberg REST catalog specification is a key component for making Iceberg tables available and discoverable by many different tools and execution engines. It enables easy integration and interaction with Iceberg table metadata via an API and also decouples metadata management from the underlying storage.

Data 84

Data Analytics Systems Review Architecture 84

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

Data Engineering 54

Data Engineering Big Data Engineering Data 54

Gorilla Logic

APRIL 27, 2022

Are you a data engineer or seeking to become one? This is the first entry of a series of articles about skills you’ll need in your everyday life as a data engineer. This blog post is for you. So let’s begin with the first and, in my opinion, the most useful tool in your technical tool belt, SQL.

Data Engineering 59

Data Engineering Engineering Data Windows 59

TechCrunch

MAY 24, 2022

Preql founders Gabi Steele and Leah Weiss were data engineers in the early days at WeWork. They later opened their own consultancy to help customers build data stacks, and they saw a stubborn consistency in the types of information their clients needed.

Data 202

Data Metrics Data Engineering Storage 202

O'Reilly Media - Data

AUGUST 16, 2018

Today’s data science and data engineering teams work with a variety of machine learning libraries, data ingestion, and data storage technologies. And as data science and data engineering teams continue to expand, tools need to enable and facilitate collaboration.

Artificial Inteligence 124

Artificial Inteligence Machine Learning Data Engineering Storage 124

Trigent

JUNE 20, 2022

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

Data Engineering 52

Data Engineering Engineering Data Strategy 52

Perficient

MARCH 27, 2025

Deletion vectors are a storage optimization feature that replaces physical deletion with soft deletion. Data privacy regulations such as GDPR , HIPAA , and CCPA impose strict requirements on organizations handling personally identifiable information (PII) and protected health information (PHI).

Compliance 52

Compliance Systems Review Policies Storage 52

TechCrunch

APRIL 12, 2022

Prior to joining Lyft, Umare was a senior software engineer at Amazon and a principal engineer at Oracle, where he led development of a block storage product for an infrastructure-as-a-service and bare metal offering.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

O'Reilly Media - Data

APRIL 3, 2018

Data Science and Machine Learning sessions will cover tools, techniques, and case studies. This year’s sessions on Data Engineering and Architecture showcases streaming and real-time applications, along with the data platforms used at several leading companies. Data platforms. Privacy and security.

Artificial Inteligence 217

Artificial Inteligence Machine Learning Company Case Study 217

TechCrunch

DECEMBER 1, 2020

And as data workloads continue to grow in size and use, they continue to become ever more complex. On top of that, today there are a wide range of applications and platforms that a typical organization will use to manage source material, storage, usage and so on. Doing so manually can be time-consuming, if not impossible.

Tools 214

Tools Data Weak Development Team Big Data 214

AWS Machine Learning - AI

NOVEMBER 20, 2024

The solution combines data from an Amazon Aurora MySQL-Compatible Edition database and data stored in an Amazon Simple Storage Service (Amazon S3) bucket. Solution overview Amazon Q Business is a fully managed, generative AI-powered assistant that helps enterprises unlock the value of their data and knowledge.

Data 111

Data AWS Groups Knowledge Base 111

CIO

FEBRUARY 13, 2023

On-prem infrastructure will grow cold — with the exception of storage, Nardecchia says. Some storage will likely stay on-prem while more is pushed into the public cloud, he says. For example, the hospital wants the ability to look at imaging and pathology data so staff can better diagnose patients faster and quicker, he says.

Budget 218

Budget Artificial Inteligence Technical Review VR 218

CIO

SEPTEMBER 2, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

In-demand skills for the role include programming languages such as Scala, Python, open-source RDBMS, NoSQL, as well as skills involving machine learning, data engineering, distributed microservices, and full stack systems. Data engineer.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

JULY 15, 2022

The forecasting systems DTN had acquired were developed by different companies, on different technology stacks, with different storage, alerting systems, and visualization layers. Working with his new colleagues, he quickly identified rebuilding those five systems around a single forecast engine as a top priority.

Systems Review 168

Systems Review Fractional CTO System Development Team Review 168