Netflix Tech

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 90

System Machine Learning Artificial Inteligence Training 90

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. Give us a holler if you are interested in a thought exchange.

Infrastructure 73

Infrastructure Scalability Cloud Data 73

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

The Citus Data

MARCH 31, 2023

Americas livestream, Citus open source user, real-time analytics, JSONB) Lessons learned: Migrating from AWS-Hosted PostgreSQL RDS to Self-Hosted Citus , by Matt Klein & Delaney Mackenzie of Jellyfish.co. (on-demand Checkpoint and WAL configs , by Samay Sharma on the Postgres open source team at Microsoft.

Azure 85

Azure Open Source Virtualization Software Engineering 85

CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Exadel

FEBRUARY 20, 2023

Vertex AI leverages a combination of data engineering, data science, and ML engineering workflows with a rich set of tools for collaborative teams. Azure Machine Learning lets you accelerate and manage ML-based projects. You can use the service to train algorithms, deploy models, and manage MLOps.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

Netflix Tech

NOVEMBER 22, 2019

December 2 1pm-2pm CMP 326-R Capacity Management Made Easy with Amazon EC2 Auto Scaling Vadim Filanovsky , Senior Performance Engineer & Anoop Kapoor, AWS Abstract :Amazon EC2 Auto Scaling offers a hands-free capacity management experience to help customers maintain a healthy fleet, improve application availability, and reduce costs.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

Netflix Tech

NOVEMBER 22, 2019

December 2 1pm-2pm CMP 326-R Capacity Management Made Easy with Amazon EC2 Auto Scaling Vadim Filanovsky , Senior Performance Engineer & Anoop Kapoor, AWS Abstract :Amazon EC2 Auto Scaling offers a hands-free capacity management experience to help customers maintain a healthy fleet, improve application availability, and reduce costs.

AWS 40

AWS Open Source Linux Off-The-Shelf 40

KitelyTech

FEBRUARY 3, 2021

Database management is what your database administrator uses to store, organize, and access computer data. It often includes three main components like the database schema, database application, and data engine. Database management systems must be flexible enough to handle large amounts of data in a short period of time.

Big Data 52

Big Data Data Development Business Intelligence 52

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Data 63

Data Software Review Technical Review Microservices 63

DataRobot

MARCH 10, 2022

With Snowflake and DataRobot, organizations can capture this data and rapidly develop artificially intelligent applications that immediately impact the bottom line. Python is unarguably the most broadly used programming language throughout the data science community. Leveraging Snowflake and DataRobot for Speed and Scale.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

TIBCO - Connected Intelligence

JULY 29, 2019

According to the Gartner Data Science Team survey, conducted at the end of 2017, even within organizations benefiting from the expertise of mature data science teams, less than half of data science projects end up being fully deployed. Best Practices to Operationalize Data Science and Machine Learning.

Innovation 26

Innovation Artificial Inteligence Machine Learning Guidelines 26

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

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. Native frameworks.

Big Data 63

Big Data Data Storage Microservices 63

Netflix Tech

NOVEMBER 22, 2019

December 2 1pm-2pm CMP 326-R Capacity Management Made Easy with Amazon EC2 Auto Scaling Vadim Filanovsky , Senior Performance Engineer & Anoop Kapoor, AWS Abstract :Amazon EC2 Auto Scaling offers a hands-free capacity management experience to help customers maintain a healthy fleet, improve application availability, and reduce costs.

AWS 15

AWS Open Source Linux Engineering Management 15

TechCrunch

NOVEMBER 2, 2022

He argues that Y42’s new DataOps Cloud will allow organizations to more easily create and run production-ready pipelines and consume the data that comes through them. Like before, Y42 fully manages the data stack, using open source tools like Airbyte to integrate the different services and dbt Core for transformations.

Data 203

Data Business Intelligence Open Source Government 203

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? Big data infrastructure in a nutshell. Staffing problems.

Big Data 116

Big Data Healthcare Applications Data 116

CIO

JULY 29, 2022

For example, if a data team member wants to increase their skills or move to a data engineer position, they can embark on a curriculum for up to two years to gain the right skills and experience. The bootcamp broadened my understanding of key concepts in data engineering.

Groups 246

Groups Security Development Data Engineering 246

Cloudera

MARCH 23, 2022

Through Cloudera’s contributions, we have extended support for Hive and Impala, delivering on the vision of a data architecture for multi-function analytics from large scale data engineering (DE) workloads and stream processing (DF) to fast BI and querying (within DW) and machine learning (ML). . 2: Open formats.

Data 92

Data Open Source Storage Machine Learning 92

Datavail

JUNE 8, 2023

From DBA to Data Engineer—The Strategic Role of DBAs in the Cloud Over the past few years, the IT landscape has experienced significant disruptions. Additionally, emerging data types and modern applications drive enterprises to adopt new data platforms. Plus, we gave away an awesome LEGO NASA Space Shuttle!

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

CIO

JUNE 14, 2023

This can be achieved by utilizing dense storage nodes and implementing fault tolerance and resiliency measures for managing such a large amount of data. Focus on scalability. First and foremost, you need to focus on the scalability of analytics capabilities, while also considering the economics, security, and governance implications.

Data 162

Data Scalability Storage Big Data 162

Cloudera

APRIL 26, 2023

Can you achieve similar outcomes with your on-premises data platform? Application modernization initiatives have led to cloud native architectures gaining popularity on premises, making it a sensible choice to extend to your data platform. You absolutely can. What is cloud native exactly?

Cloud 65

Cloud Data Load Balancer Storage 65

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. Amazon Kinesis.

Analytics 20

Analytics Data IoT Analysis 20

Cloudera

NOVEMBER 19, 2020

Too often, though, legacy systems cannot deliver the needed speed and scalability to make these analytic defenses usable across disparate sources and systems. For many agencies, 80 percent of the work in support of anomaly detection and fraud prevention goes into routine tasks around data management.

Government 117

Government Artificial Inteligence Machine Learning Data 117

Altexsoft

MAY 14, 2021

Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. It comes in all sorts of forms that differ from one application to another, and most of Big Data is unstructured. Source: phoenixNAP.

Big Data 78

Big Data Analytics Tools Applications 78

Apiumhub

SEPTEMBER 20, 2023

Tech Conferences Compass Tech Summit – October 5-6 Compass Tech Summit is a remarkable 5-in-1 tech conference, encompassing topics such as engineering leadership, AI, product management, UX, and data engineering that will take place on October 5-6 at the Hungarian Railway Museum in Budapest, Hungary.

Conference 97

Conference Artificial Inteligence UI/UX Machine Learning 97

Altexsoft

DECEMBER 14, 2022

Docker is an open-source containerization software platform: It is used to create, deploy and manage applications in virtualized containers. With the help of Docker, applications including their environment can be provided in parallel and isolated from one another on a host system. scaling application environments.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Scalability. Source: Qubole.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. Source: Apache Airflow.

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Users that have their own self-managed Airflow instances, can also use CDP operators.

Data 111

Data Open Source Government Analytics 111

Cloudera

DECEMBER 20, 2023

In this post we’ll give you an overview of these new and expanded partnerships and how we see them fitting into the emerging AI technology stack that supports the AI application lifecycle. We see AI applications like chatbots being built on top of closed-source or open source foundational models.

Artificial Inteligence 73

Artificial Inteligence Artificial Intelligence Enterprise Machine Learning 73

Altexsoft

JULY 18, 2023

Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics. With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Altexsoft

OCTOBER 8, 2021

On the enterprise level, data integration may cover a wider array of data management tasks including. application integration — the process of enabling individual applications to communicate with one another by exchanging data. On-premise data integration tools. Open-source data integration tools.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. It depends on the volume of incoming data.

Big Data 59

Big Data Data Google Cloud Storage 59

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 97

Strategy Data Technical Review Weak Development Team 97

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Use cases: small projects, specific source and target locations not supported by other solutions. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. Use cases: moving data from on-premises to cloud or between cloud environments.

Software Review 69

Software Review Software Data Technical Review 69

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Read why the future of data lakehouses is open.

Data 87

Data Analytics Machine Learning Artificial Inteligence 87