CTOvision

MAY 1, 2014

Senior Software Engineer – Big Data. IO is the global leader in software-defined data centers. IO has pioneered the next-generation of data center infrastructure technology and Intelligent Control, which lowers the total cost of data center ownership for enterprises, governments, and service providers.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

Netflix Tech

JUNE 1, 2021

Data Engineers of Netflix?—?Interview Interview with Samuel Setegne Samuel Setegne 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. What drew you to Netflix?

Data Engineering 52

Data Engineering Engineering Data Culture 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 358

LAN Systems Administration How To WAN 358

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. User data collection is data about a user who is collected for market research purposes.

Big Data 52

Big Data Data Development Business Intelligence 52

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

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. Another sign of its growth is a big hire that the company is making. billion valuation.

Analytics 218

Analytics Data Big Data Business Intelligence 218

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

Big Data 63

Big Data Data Storage Microservices 63

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Data Platforms. Data Integration and Data Pipelines. Model lifecycle management.

Big Data 85

Big Data Technology Tools Cloud 85

Cloudera

DECEMBER 1, 2017

If you’re going to Strata Data Singapore 2017 at the Suntec Singapore Convention & Exhibition Centre , here are four sessions to attend that cover various combinations of my favorite themes: big data, safe data, and cloud data. A deep dive into r unning big data workloads in the cloud.

Big Data 40

Big Data Data Cloud Government 40

Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Watch our video explaining how data engineering works.

Architecture 52

Architecture Data Storage Machine Learning 52

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. From architectures and databases to feature stores and feature engineering, a myriad of variables must work in sync for this to be accomplished.

Artificial Inteligence 291

Artificial Inteligence Strategy Data Machine Learning 291

Cloudera

JUNE 7, 2022

Big data is cool again. As the company who taught the world the value of big data, we always knew it would be. But this is not your grandfather’s big data. It has evolved into something new – hybrid data. Where data flows, ideas follow. Today, we are leading the way in hybrid data.

Data 106

Data Architecture Analytics Government 106

Cloudera

JULY 27, 2021

While billing used to be one of two critical things for any successful telco (the other being the network), today’s digital service providers prioritise channels, ecosystems, payments and cloud service architectures in enterprise architecture. Big Data has long been a growth area in telecom,’ he told me.

Telecommunications 60

Telecommunications Data Architecture Big Data 60

Altexsoft

MAY 27, 2020

Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements. Reasonably, with the access to data, anyone with a computer can train a machine learning model today.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. But it requires a different engineering approach and not just because of its amount. Data engineering vs big data engineering.

Big Data 75

Big Data Data Engineering Engineering Data 75

TechCrunch

SEPTEMBER 29, 2022

.” Coalesce offers tools designed to simplify modeling, cleansing and governance of data primarily in the Snowflake cloud, powered by what Petrossian describes as a “column-aware” architecture that leverages metadata to manage data transformations with an understanding of how the data is related or connected.

Enterprise 184

Enterprise Data Business Intelligence Analytics 184

Dzone - DevOps

FEBRUARY 16, 2023

So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses. Too Much Data on My Plate The choice of data warehouses was never high on my worry list until 2021. In the company's infancy, we didn't have too much data to juggle.

Data 71

Data ChatGPT Storage Architecture 71

Apiumhub

FEBRUARY 6, 2023

In this event, hundreds of innovative minds, enterprise practitioners, technology providers, startup founders, and innovators come together to discuss ideas on data science, big data, ML, AI, data management, data engineering, IoT, and analytics.

Innovation 82

Innovation Data Machine Learning Artificial Inteligence 82

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Big Data is Not Just More Data : That’s because the nature of the data we can now collect has changed.

Big Data 33

Big Data Data Storage Journal 33

CIO

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

ChatGPT 130

ChatGPT Government Artificial Inteligence Business Intelligence 130

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

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. Compared to previous CPU-based architectures, CDP 7.1

Enterprise 87

Enterprise Cloud Data Machine Learning 87

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data 89

Data Analytics Open Source Architecture 89

Apiumhub

NOVEMBER 17, 2022

Speakers include: Simon Brown – Creator of the famous C4 model, Author of “Software Architecture for Developers” & Founder of Structurizr. Jesse Anderson – Data Engineer, Creative Engineer, and Managing Director of Big Data Institute. Jonas Mayer – Senior Consultant at TNG Technology.

Technical Review 79

Technical Review Software Review Fractional CTO CTO Coach 79

CTOvision

JANUARY 28, 2015

We''ve added new sessions and tracks to reflect challenges that have emerged in the data field— including security, ubiquitous computing, collaboration, reproducibility, new interfaces, emerging architecture, building data teams, machine data —and much more. Data scientists. Data engineers.

Big Data 109

Big Data Case Study Conference Study 109

Mobilunity

MAY 8, 2023

It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Ingestion zone is where data is collected from various sources and ingested into the data lake.

Engineering 52

Engineering Data Storage AWS 52

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

CTOvision

FEBRUARY 23, 2017

This is the place to dive deep into the latest on Big Data, Analytics, Artificial Intelligence, IoT, and the massive cybersecurity issues in all those topics. If you want to tap into the opportunity that big data presents, you want to be there. Find new ways to leverage your data assets across industries and disciplines.

Big Data 61

Big Data Artificial Intelligence Artificial Inteligence Case Study 61

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 83

Innovation Data Technical Review Artificial Inteligence 83

Cloudera

SEPTEMBER 10, 2021

Now, the agency is turning a corner on putting its mass quantities of data to work, collaborating with enterprise data engineers in industry to utilize those data troves to better protect taxpayers. Pairing High-Tech Keys to Unlock the Power of Data.

Artificial Inteligence 66

Artificial Inteligence Machine Learning Artificial Intelligence Engineering 66

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

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

O'Reilly Media - Ideas

JUNE 4, 2019

Understanding Data Science Algorithms in R: Scaling, Normalization and Clustering , August 14. Real-time Data Foundations: Spark , August 15. Visualization and Presentation of Data , August 15. Python Data Science Full Throttle with Paul Deitel: Introductory AI, Big Data and Cloud Case Studies , September 24.

Course 64

Course Training Artificial Inteligence Software Review 64

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

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 117

Artificial Inteligence Generative AI Security Applications 117

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100