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

CIO

FEBRUARY 13, 2023

For example, New York-Presbyterian Hospital, which has a network of hospitals and about 2,600 beds, is deploying over 150 AI and VR/AR projects this year across all clinical specialties. Cold: On-prem infrastructure As they did in 2022, many IT leaders are reducing investments in data centers and on-prem technologies. “We

Budget 218

Budget Artificial Inteligence Technical Review VR 218

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. Splunk acquires network observability service Flowmill.

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

Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems. A REST API is built directly into our VSP storage controllers.

Systems Review 72

Systems Review Storage System Software Review 72

O'Reilly Media - Data

JULY 18, 2018

I list a few examples from the media industry, but there are are numerous new startups that collect aerial imagery, weather data, in-game sports data , and logistics data, among other things. If you are an aspiring entrepreneur, note that you can build interesting and highly valued companies by focusing on data.

Artificial Inteligence 196

Artificial Inteligence Machine Learning Data Marketing 196

CIO

JUNE 22, 2023

Every business unit has a stake in the IT services, apps, networks, hardware, and software needed to meet business goals and objectives, and many of them are hiring their own technologists. The industry has a demand for highly-skilled IT pros who have the skills and knowledge to navigate complex and technical systems and networks.

Industry 183

Industry UI/UX Telecommunications Quality Assurance 183

Linux Academy

MAY 7, 2019

Microsoft Certified Azure AI Engineer Associate ( Associate ). Microsoft Certified Azure Data Engineer Associate ( Associate ). It includes major services related to compute, storage, network, and security, and is aimed at those in administrative and technical roles looking to validate administration knowledge in cloud services.

Azure 150

Azure Linux Technical Review Course 150

CIO

JUNE 7, 2022

Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. Data analytics and data science are closely related.

Analytics 203

Analytics Data Analysis Business Analytics 203

CIO

JULY 6, 2023

OCI’s Supercluster includes OCI Compute Bare Metal, which provides an ultralow-latency remote direct access memory (RDMA) over a Converged Ethernet (RoCE) cluster for low-latency networking, and a choice of high-performance computing storage options.

Generative AI 170

Generative AI Artificial Inteligence Strategy Google Cloud 170

Kentik

APRIL 12, 2023

Network telemetry and DataOps are two concepts that play a critical role in enhancing network visibility. With modern networks’ increasing complexity and scale, it has become essential to collect and analyze data from various sources to gain insights into network performance, security, and availability.

Network 52

Network Data Engineering Artificial Inteligence Machine Learning 52

CIO

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam consists of 60 questions and the candidate has 90 minutes to complete it.

Artificial Inteligence 190

Artificial Inteligence Data Machine Learning Azure 190

Linux Academy

MAY 7, 2019

Microsoft Certified Azure AI Engineer Associate ( Associate ). Microsoft Certified Azure Data Engineer Associate ( Associate ). It includes major services related to compute, storage, network, and security, and is aimed at those in administrative and technical roles looking to validate administration knowledge in cloud services.

Azure 134

Azure Linux Technical Review Course 134

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so? Scalability opportunities.

Backup 115

Backup Azure Software Review Architecture 115

Kentik

MAY 10, 2023

A unified data repository (UDR) is a centralized storage system that consolidates, organizes, and manages data from different sources. It serves as a single point of access for various types of data, which could be a significant volume of very diverse data formats in an extensive network.

Analytics 59

Analytics Network Data Artificial Inteligence 59

Kentik

FEBRUARY 7, 2023

But what are network operators to do when their cloud networks have to be distributed, both architecturally and geographically? Suddenly, this dense data mass is a considerable burden, and the same forces that happily drew in service and customer data find that that data is now trapped and extremely expensive and complicated to move.

Network 59

Network Cloud Data Data Center 59

Tenable

NOVEMBER 3, 2022

When our data engineering team was enlisted to work on Tenable One, we knew we needed a strong partner. When Tenable’s product engineering team came to us in data engineering asking how we could build a data platform to power the product, we knew we had an incredible opportunity to modernize our data stack.

Data 98

Data AWS Storage Data Engineering 98

Kentik

MAY 31, 2023

In the first part of this series , I introduced network reliability as a concept foundational to success for IT and business operations. I also pointed out that because of necessary factors like redundancy, the pursuit of reliability will inevitably mean making compromises that affect a network’s cost or performance.

Network 52

Network Cloud Load Balancer Systems Review 52

CIO

JUNE 14, 2023

Start with storage. Before you can even think about analyzing exabytes worth of data, ensure you have the infrastructure to store more than 1000 petabytes! Going from 250 PB to even a single exabyte means multiplying storage capabilities four times. So, what does it require for organizations to go from PB to EB scale?

Data 97

Data Scalability Storage Big Data 97

Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87

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.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

Kentik

MAY 23, 2017

Why Every ISP Needs a Robust Network Monitoring Solution. To do that in today’s network environment, ISPs need deeper network visibility. It used to be that cloud-scale network monitoring was within reach of only the biggest, richest organizations, those that were most software-savvy and R&D-heavy.

Network 40

Network Open Source Big Data Load Balancer 40

Cloudera

AUGUST 26, 2020

Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information. Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform.

Data 84

Data Artificial Inteligence Machine Learning Disaster Recovery 84

Kentik

JUNE 13, 2016

Kentik delves deeper into your data for detection and defense. According to 2015 research reports published by Ponemon, Mandiant, and others, the median pre-detection dwell time for an intruder in a target network ranges at around 200 days. Reducing a network's intruder dwell time is mostly about detection.

Network 40

Network LAN Big Data WAN 40

Kentik

JULY 18, 2016

Irwin’s story may be interesting, but what does it have to do with network traffic data? The answer is rooted in the experience of Kentik’s founders, who’ve spent decades building and operating some of the world’s biggest and most complex networks. I wrote previously about this kind of potential in Moneyball Your Network.)

Big Data 40

Big Data Network Analytics Data 40

Hu's Place - HitachiVantara

MAY 10, 2019

For this reason, many financial institutions are converting their fraud detection systems to machine learning and advanced analytics and letting the data detect fraudulent activity. This will require another product for data governance. Data Preparation : Data integrationthat is intuitive and powerful.

Data 90

Data Artificial Inteligence Machine Learning Weak Development Team 90

Cloudera

NOVEMBER 2, 2020

Having a live view of all aspects of their network lets them identify potentially faulty hardware in real time so they can avoid impact to customer call/data service. Ingest 100s of TB of network event data per day . Updates and deletes to ensure data correctness. Basic Architecture for Real-Time Data Warehousing.

Data 97

Data Analytics Storage Big Data 97

Kentik

MAY 31, 2017

Freeing Your Network Teams From Legacy Limits. At Kentik, we firmly believe that network engineering, operations, and planning are critically dependent not only on the quality of traffic data but also the accessibility of that data. Unfortunately, that’s pretty much the status quo for network teams today.

Network 40

Network Tools Big Data Engineering 40

Altexsoft

NOVEMBER 23, 2020

Otherwise, let’s start from the most basic question: What is data migration? What is data migration? In general terms, data migration is the transfer of the existing historical data to new storage, system, or file format. What makes companies migrate their data assets. Main types of data migration.

Data 104

Data Transportation Backup Storage 104

Cloudera

FEBRUARY 12, 2024

Most Azure users use hub-spoke network topology. DNS servers are usually deployed in the hub virtual network or an on-prem data center instead of in the Cloudera VNET. Service endpoint is a simpler implementation to allow resources on a private network to access managed services on Azure Cloud.

Azure 52

Azure Firewall Data Engineering Storage 52

Altexsoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. Virtually, Hadoop puts no limits on the storage capacity. What is Hadoop.

Big Data 98

Big Data Tools Data Storage 98

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. Edge analytics by definition require in-network deployment.

Telecommunications 64

Telecommunications Data Architecture Big Data 64

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. Storage provisioning.

Big Data 63

Big Data Data Storage Microservices 63

AWS Machine Learning - AI

JULY 10, 2024

With App Studio, a user simply describes the application they want, what they want it to do, and the data sources they want to integrate with, and App Studio builds an application in minutes that could have taken a professional developer days to build a similar application from scratch.

Artificial Inteligence 142

Artificial Inteligence AWS Generative AI Knowledge Base 142

Prisma Clud

JANUARY 15, 2025

In this article, well look at how you can use Prisma Cloud DSPM to add another layer of security to your Databricks operations, understand what sensitive data Databricks handles and enable you to quickly address misconfigurations and vulnerabilities in the storage layer.

Artificial Inteligence 52

Artificial Inteligence Cloud Data Storage 52

Hu's Place - HitachiVantara

JANUARY 3, 2019

Data curation will be a focus to understand the meaning of the data as well as the technologies that are applied to the data so that data engineers can move and transform the essential data that data consumers need to power the organization.

Trends 86

Trends Artificial Inteligence Machine Learning Data Center 86

O'Reilly Media - Ideas

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. This shift requires a fundamental change in your software engineering practice.

Product Management 145

Product Management Artificial Inteligence Machine Learning Weak Development Team 145