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.

Systems 90

Systems Media Machine Learning Data Warehouse 90

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. Missing data?

Systems 100

Systems Building Metadata Data Warehouse 100

Data Engineering Podcast

SEPTEMBER 11, 2022

Summary Data engineering systems are complex and interconnected with myriad and often opaque chains of dependencies. In order to turn this into a tractable problem one approach is to define and enforce contracts between producers and consumers of data. Atlan is the metadata hub for your data ecosystem.

Systems 100

Systems Metadata Building MongoDB 100

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. RudderStack’s smart customer data pipeline is warehouse-first. How does it work?

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Knowledge Hut

APRIL 25, 2024

Intrusion detection systems (IDS) are designed to identify suspicious and malicious activity through network traffic. So, let's get to know the meaning of an intrusion detection system and how it works. What Is a n Intrusion Detection System? Why Are Intrusion Detection Systems Important? and how it works.

Systems 52

Systems Recruitment Machine Learning Certification 52

Data Engineering Podcast

APRIL 22, 2018

Summary The information about how data is acquired and processed is often as important as the data itself. For this reason metadata management systems are built to track the journey of your business data to aid in analysis, presentation, and compliance. What is involved in deploying your metadata collection agents?

Business Intelligence 113

Business Intelligence Metadata Management Data Governance 113

Data Engineering Podcast

AUGUST 13, 2022

Summary Data is useless if it isn’t being used, and you can’t use it if you don’t know where it is. Data catalogs were the first solution to this problem, but they are only helpful if you know what you are looking for. Data stacks are becoming more and more complex. Sifflet also offers a 2-week free trial.

Metadata 100

Metadata MongoDB Scala MySQL 100

Data Engineering Podcast

APRIL 24, 2022

Summary There are very few tools which are equally useful for data engineers, data scientists, and machine learning engineers. WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model.

Machine Learning 100

Machine Learning Systems Data Lake Metadata 100

Precisely

MAY 13, 2024

Key Takeaways: Data integration is vital for real-time data delivery across diverse cloud models and applications, and for leveraging technologies like generative AI. As enterprise technology landscapes grow more complex, the role of data integration is more critical than ever before.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

Snowflake

MAY 15, 2024

According to Infosys, 35% of AI projects will either fail or experience delays because of poor data quality. There’s a huge gap between the data quality most companies have by default and the data quality needed for successful AI. And that gap is directly affecting the performance and reliability of AI systems everywhere.

Cloud 90

Cloud Metadata Data Pipeline Government 90

Netflix Tech

SEPTEMBER 29, 2022

Timestone: Netflix’s High-Throughput, Low-Latency Priority Queueing System with Built-in Support for Non-Parallelizable Workloads by Kostas Christidis Introduction Timestone is a high-throughput, low-latency priority queueing system we built in-house to support the needs of Cosmos , our media encoding platform. Over the past 2.5

Systems 85

Systems Metadata Media Kafka 85

Data Engineering Podcast

NOVEMBER 6, 2022

Summary A lot of the work that goes into data engineering is trying to make sense of the "data exhaust" from other applications and services. Atlan is the metadata hub for your data ecosystem. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Building 130

Building IT Metadata MongoDB 130

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 105

Data Engineering Data Engineer Engineering Metadata 105

Data Engineering Podcast

JULY 5, 2021

Summary At the core of every data pipeline is an workflow manager (or several). Deploying, managing, and scaling that orchestration can consume a large fraction of a data team’s energy so it is important to pick something that provides the power and flexibility that you need.

Systems 100

Systems Management Data Warehouse Programming Language 100

Booking.com Engineering

DECEMBER 2, 2022

From data ingestion, data science, to our ad bidding[2], GCP is an accelerant in our development cycle, sometimes reducing time-to-market from months to weeks. Data Ingestion and Analytics at Scale Ingestion of performance data, whether generated by a search provider or internally, is a key input for our algorithms.

Systems 52

Systems Cloud MySQL Relational Database 52

Data Engineering Weekly

MARCH 24, 2024

link] Kai Waehner: The Data Streaming Landscape 2024 This is a comprehensive overview of the state of the data streaming landscape in 2024. The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Ascend.io

APRIL 22, 2024

At Ascend, we believe it’s time to rethink data engineering from the ground up. As the world of data continues to evolve at a breakneck pace, we are thrilled to announce the next revolutionary step in our journey – Project Inception. Read More: The State of Data Engineering in 2023: Does Your Data Program Stack Up?

Project 52

Project Metadata Data Pipeline Data Engineering 52

Netflix Tech

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 103

Data Engineering Data Engineer Engineering Metadata 103

Data Engineering Podcast

FEBRUARY 26, 2023

Summary There has been a lot of discussion about the practical application of data mesh and how to implement it in an organization. Jean-Georges Perrin was tasked with designing a new data platform implementation at PayPal and wound up building a data mesh. Is a data mesh ever "done"? We feel your pain.

Building 147

Building Metadata Machine Learning Data Integration 147

Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

DECEMBER 4, 2022

Summary Business intelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for business intelligence. Atlan is the metadata hub for your data ecosystem. And don’t forget to thank them for their continued support of this show!

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Data Engineering Podcast

JUNE 19, 2022

Summary Data analysis is a valuable exercise that is often out of reach of non-technical users as a result of the complexity of data systems. Atlan is the metadata hub for your data ecosystem. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Atlan is the metadata hub for your data ecosystem.

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

JUNE 5, 2022

Summary The best way to make sure that you don’t leak sensitive data is to never have it in the first place. The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

JULY 10, 2022

Summary Building a data platform is a journey, not a destination. In this episode Inbar Yogev and Lior Winner share the journey that they and their teams at Riskified have been on for their data platform. They also discuss how they have established a guild system for training and supporting data professionals in the organization.

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

AUGUST 6, 2022

Summary Data mesh is a frequent topic of conversation in the data community, with many debates about how and when to employ this architectural pattern. The team at AgileLab have first-hand experience helping large enterprise organizations evaluate and implement their own data mesh strategies.

Metadata 100

Metadata MongoDB MySQL Business Intelligence 100

Knowledge Hut

MARCH 7, 2024

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale. What and Where is Data Quality?

Big Data 84

Big Data Metadata Data Warehouse Data 84

Data Engineering Podcast

AUGUST 28, 2022

For data engineers, this is a monumental undertaking. Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The only thing worse than having bad data is not knowing that you have it.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

Monte Carlo

APRIL 20, 2024

That’s where you really want to focus your data quality monitoring.” And it’s true – you need to go “deep” on certain data sets; but if you’re not monitoring broadly as well, you’re missing the boat—and a whole lot of bad data. What is data quality monitoring?

IT 52

IT Metadata Data Warehouse BI 52

Data Engineering Weekly

MARCH 10, 2024

Editor’s Note: Chennai Meetup Wrap-Up & Preparation work started for DEWCon I am so grateful for the enthusiastic participants who made our Chennai Data Heroes- Community for Data Folks meetup vibrant! Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

LinkedIn Engineering

DECEMBER 19, 2023

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. Historically, deploying code changes to Hadoop big data clusters has been complex.

Big Data 92

Big Data Hadoop Metadata Data 92

Data Engineering Weekly

NOVEMBER 11, 2022

I took a break from data engineering and focused on system monitoring and observability for some time. Little did I know I would be building data pipelines to measure system efficiency instead of measuring business efficiency. As the famous saying goes; Once a data engineer, always a data engineer.

Systems 40

Systems High Quality Data Consulting Metadata 40

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Ascend.io

FEBRUARY 28, 2024

The rise of generative AI is changing more than just technology; it’s reshaping our professional landscapes — and yes, data engineering is directly experiencing the impact. How does AI recalibrate the workload and priorities of data teams? How can data engineers harness the power of AI?

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52