Netflix Tech

DECEMBER 3, 2022

by Jasmine Omeke , Obi-Ike Nwoke , Olek Gorajek Intro This post is for all data practitioners, who are interested in learning about bootstrapping, standardization and automation of batch data pipelines at Netflix. You may remember Dataflow from the post we wrote last year titled Data pipeline asset management with Dataflow.

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Data Pipeline Scala Metadata Food 144

Christophe Blefari

MARCH 15, 2024

Cognition AI introduced Devin — Devin is the first AI software engineer, Devin can, unassisted, do software engineering tasks like fixing Github issues (13% of success, previously best was ~5%), apply to jobs on Upwork, train and fine-tune its own models. Arrow doing a lot of the data operation heavy lifting.

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Metadata Datasets Data Data Warehouse 272

Databand.ai

JUNE 28, 2023

Data Pipeline Observability: A Model For Data Engineers Eitan Chazbani June 29, 2023 Data pipeline observability is your ability to monitor and understand the state of a data pipeline at any time. We believe the world’s data pipelines need better data observability.

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Data Engineering Podcast

MARCH 10, 2023

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Join in with the event for the global data community, Data Council Austin. As a listener to the Data Engineering Podcast you can get a special discount of 20% off your ticket by using the promo code dataengpod20.

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Data Warehouse Data Lake Machine Learning Data Science 130

Cloudera

FEBRUARY 8, 2021

Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1): Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a vehicle showroom). STEP 3: Send data to Cloudera Data Warehouse.

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Data Pipeline Building Manufacturing Data Warehouse 122

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.

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Data Pipeline Data Engineering Data Engineer Engineering 105

Start Data Engineering

OCTOBER 12, 2021

Introduction Responsibilities of a data engineer 1. Move data between systems 2. Manage data warehouse 3. Schedule, execute, and monitor data pipelines 4. Serve data to the end-users 5. Data strategy for the company 6.

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Data Engineering Data Engineer Engineering Data Warehouse 130

Christophe Blefari

JANUARY 20, 2024

Learn data engineering, all the references ( credits ) This is a special edition of the Data News. But right now I'm in holidays finishing a hiking week in Corsica 🥾 So I wrote this special edition about: how to learn data engineering in 2024. Who are the data engineers?

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Simon Späti

MARCH 9, 2021

This post focuses on practical data pipelines with examples from web-scraping real-estates, uploading them to S3 with MinIO, Spark and Delta Lake, adding some Data Science magic with Jupyter Notebooks, ingesting into Data Warehouse Apache Druid, visualising dashboards with Superset and managing everything with Dagster.

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Data Engineering Data Engineer Engineering Project 130

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. We’ll answer the question, “What are data pipelines?” Table of Contents What are Data Pipelines?

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Data Engineering Podcast

OCTOBER 28, 2021

In this episode Eric Sammer discusses the shortcomings of the current set of streaming engines and how they force engineers to work at an extremely low level of abstraction. Data engineers struggling with unreliable data need look no further than Monte Carlo, the world’s first end-to-end, fully automated Data Observability Platform!

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Data Engineering Podcast

FEBRUARY 8, 2021

In this episode Zeeshan Qureshi and Michelle Ark share their experiences using DBT to manage the data warehouse for Shopify. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code. What kinds of data sources are you working with?

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Data Warehouse Building BI SQL 100

Data Engineering Podcast

JANUARY 1, 2022

In this episode Emily Riederer shares her work to create a controlled vocabulary for managing the semantic elements of the data managed by her team and encoding it in the schema definitions in her data warehouse. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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Data Warehouse BI Data Workflow Data Engineering 100

Data Engineering Podcast

JUNE 4, 2023

Summary A significant portion of the time spent by data engineering teams is on managing the workflows and operations of their pipelines. Agile Data Engine is a platform designed to handle the infrastructure side of the DataOps equation, as well as providing the insights that you need to manage the human side of the workflow.

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Data Engineering Podcast

APRIL 19, 2021

Summary Most of the time when you think about a data pipeline or ETL job what comes to mind is a purely mechanistic progression of functions that move data from point A to point B. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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Data Pipeline Machine Learning Data Warehouse Datasets 100

Data Engineering Podcast

JUNE 1, 2021

Summary Every part of the business relies on data, yet only a small team has the context and expertise to build and maintain workflows and data pipelines to transform, clean, and integrate it. RudderStack’s smart customer data pipeline is warehouse-first.

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Data Engineering Podcast

JANUARY 18, 2021

Summary The data warehouse has become the central component of the modern data stack. This is an interesting conversation about the importance of the data warehouse and how it can be used beyond just internal analytics. How do you keep data up to date between the warehouse and downstream systems?

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Data Engineering Podcast

MAY 1, 2022

He describes how the platform is architected, the challenges related to selling cloud technologies into enterprise organizations, and how you can adopt Matillion for your own workflows to reduce the maintenance burden of data integration workflows. Struggling with broken pipelines? Missing data? Stale dashboards?

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Data Engineering Weekly

JUNE 10, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. Databricks and Snowflake offer a data warehouse on top of cloud providers like AWS, Google Cloud, and Azure.

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Data Engineering Data Engineer Engineering Kafka 104

Data Engineering Podcast

FEBRUARY 4, 2024

RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage layer. In this episode Yingjun Wu explains how it is architected to power analytical workflows on continuous data flows, and the challenges of making it responsive and scalable.

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Data Engineering Weekly

MAY 16, 2023

I won’t bore you with the importance of data quality in the blog. Instead, Let’s examine the current data pipeline architecture and ask why data quality is expensive. Instead of looking at the implementation of the data quality frameworks, Let's examine the architectural patterns of the data pipeline.

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Engineering Kafka Data Pipeline Data Warehouse 112

Data Engineering Podcast

APRIL 9, 2023

Now that the data warehouse has taken center stage a new approach of composable customer data platforms is emerging. In this episode Darren Haken is joined by Tejas Manohar to discuss how Autotrader UK is addressing their customer data needs by building on top of their existing data stack.

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Data Lake Data Warehouse Machine Learning Data 147

Data Engineering Podcast

JANUARY 21, 2024

In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).

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Data Lake High Quality Data NoSQL Data Warehouse 147

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.

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Data Engineering Data Engineer Engineering Data Warehouse 83

Data Engineering Podcast

DECEMBER 28, 2022

In this episode he shares his thoughts on the strategic and tactical elements of moving your work as a data professional from being task-oriented to being product-oriented and the long term improvements in your productivity that it provides. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

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Data Lake Data Warehouse Data Pipeline MongoDB 130

Data Engineering Podcast

JANUARY 15, 2022

In this episode Brian McMillan shares his work on the book "Building Data Products" and how he is working to educate business users and data professionals about the combination of technical, economical, and business considerations that need to be blended for these projects to succeed.

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Engineering Electronics Data Pipeline ETL Tools 100

Data Engineering Podcast

OCTOBER 22, 2021

One of the driving forces for that change has been the rise of analytics engineering powered by dbt. Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. No more scripts, just SQL.

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Engineering Business Intelligence BI Data Warehouse 100

Data Engineering Podcast

DECEMBER 25, 2022

In this episode he shares the work that he and his team have done to simplify integration of secure enclaves and trusted computing environments into analytical workflows and how you can start using it without re-engineering your existing systems. RudderStack helps you build a customer data platform on your warehouse or data lake.

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Data Engineering Podcast

MAY 28, 2023

Ghalib Suleiman has been on both sides of this equation and joins the show to share his hard-won wisdom about how to start and grow a data team in the early days of company growth. Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform. Support Data Engineering Podcast

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Data Lake Machine Learning Data Warehouse Education 162

Data Engineering Weekly

MAY 26, 2024

[link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. It is a long standing question on people wondering In what situations should you use SQL instead of Pandas as a data scientist?

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Data Engineering Data Engineer Engineering Google Cloud 78

Data Engineering Podcast

MAY 21, 2023

Summary Batch vs. streaming is a long running debate in the world of data integration and transformation. Proponents of the streaming paradigm argue that stream processing engines can easily handle batched workloads, but the reverse isn't true. Stream processing technologies have been around for around a decade.

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Data Lake Machine Learning Kafka Data Warehouse 162

Ascend.io

NOVEMBER 14, 2024

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. Resilience and adaptability are the cornerstones of a future-proof data pipeline.

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Data Engineering Podcast

JUNE 9, 2024

Summary Streaming data processing enables new categories of data products and analytics. Unfortunately, reasoning about stream processing engines is complex and lacks sufficient tooling. Data lakes are notoriously complex. My thanks to the team at Code Comments for their support.

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Data Engineering Podcast

MAY 14, 2023

In this episode the host Tobias Macey shares his reflections on recent experiences where the abstractions leaked and some observances on how to deal with that situation in a data platform architecture. Rudderstack]([link] RudderStack provides all your customer data pipelines in one platform. Support Data Engineering Podcast

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Data Lake Machine Learning Data Warehouse AWS 147

Data Engineering Podcast

SEPTEMBER 19, 2021

In this episode Jillian Rowe shares her experience of working in the field and supporting teams of scientists and analysts with the data infrastructure that they need to get their work done. This is a fascinating exploration of the collaboration between data professionals and scientists. Missing data? Stale dashboards?

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Data Engineering Data Engineer Engineering Data Lake 100

AltexSoft

OCTOBER 30, 2021

Was Nikola Tesla a scientist or engineer? These men didn’t stop at scientific research and ended up conceptualizing or engineering their inventions. Engineers are not only the ones bearing helmets and operating on construction sites. Data science vs data engineering. How about Edison? Or Da Vinci?

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Data Engineering Data Engineer Engineering Machine Learning 98

Data Engineering Weekly

JULY 7, 2024

Experience Enterprise-Grade Apache Airflow Astro augments Airflow with enterprise-grade features to enhance productivity, meet scalability and availability demands across your data pipelines, and more. The author highlights Paimon’s consistency model by examining the metadata model.

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