Netflix Tech

DECEMBER 3, 2022

This is one way to build trust with our internal user base. Obviously not all tools are made with the same use case in mind, so we are planning to add more code samples for other (than classical batch ETL) data processing purposes, e.g. Machine Learning model building and scoring. backfill.sch.yaml ??? daily.sch.yaml ???

Data Pipeline 144

Data Pipeline Scala Metadata Food 144

Data Engineering Podcast

AUGUST 13, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Metadata 100

Metadata MongoDB MySQL Scala 100

Data Engineering Podcast

SEPTEMBER 11, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Systems 100

Systems Metadata Building MongoDB 100

Data Engineering Podcast

FEBRUARY 19, 2023

It's supposed to make building smarter, faster, and more flexible data infrastructures a breeze. By bringing all the layers of the data stack together, TimeXtender helps you build data solutions up to 10 times faster and saves you 70-80% on costs. Acryl]([link] The modern data stack needs a reimagined metadata management platform.

IT 147

IT Data Lake Metadata Data Warehouse 147

Data Engineering Podcast

OCTOBER 28, 2019

In an effort to create a better abstraction for building data applications Nick Schrock created Dagster. In this episode he explains his motivation for creating a product for data management, how the programming model simplifies the work of building testable and maintainable pipelines, and his vision for the future of data programming.

Building 100

Building Data Pipeline Programming Language Kafka 100

Data Engineering Podcast

NOVEMBER 9, 2020

Summary A data catalog is a critical piece of infrastructure for any organization who wants to build analytics products, whether internal or external. While there are a number of platforms available for building that catalog, many of them are either difficult to deploy and integrate, or expensive to use at scale.

Building 100

Building PostgreSQL BI Metadata 100

Snowflake

OCTOBER 2, 2023

To help customers overcome these challenges, RudderStack and Snowflake recently launched Profiles , a new product that allows every data team to build a customer 360 directly in their Snowflake Data Cloud environment. Now teams can leverage their existing data engineering tools and workflows to build their customer 360.

Cloud 106

Cloud Building Insurance Data Engineering 106

The Pragmatic Engineer

AUGUST 3, 2023

Now after 7 years, Google has announced it will retire Firebase Dynamic Links, but with no definite successor lined up. ” Because of how useful this product is, especially for app developers building on top of it, this announcement came as a surprise. We will announce more information in Q3 2023.”

Metadata 162

Metadata Engineering Building Technology 162

Netflix Tech

FEBRUARY 16, 2021

The original SKU catalog is a logic-heavy client library packaged with complex metadata configuration files and consumed by various services. Operational Efficiency: The majority of the changes require metadata configuration files and library code changes, usually taking days of testing and service release to adopt the updates.

Building 87

Building Management Metadata Entertainment 87

Netflix Tech

MARCH 25, 2019

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can push or pull.

Building 90

Building Metadata Transportation Data Ingestion 90

François Nguyen

MARCH 22, 2021

How do we build data products ? This is really for us the definition of a self serve platform. ” Code : all the code necessary to build a data product (data pipelines, API, policies). As you can see, this is in the code part where you are building your data pipelines, a misnomer because this is an over simplification.

Technology 130

Technology Architecture Google Cloud Metadata 130

Data Engineering Podcast

MAY 22, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. What do you see as the closest alternatives?

Machine Learning 130

Machine Learning Data Engineer Data Engineering Cloud 130

ThoughtSpot

OCTOBER 9, 2023

ThoughtSpot continually invests in this area, giving users the confidence to build the correct Answers needed for their analysis—and ensuring they can trust the data they are shown. How ThoughtSpot builds trust with data catalog connectors For many, the data catalog is still the primary home for metadata enrichment and governance.

Metadata 105

Metadata Government Data Data Governance 105

Tweag

NOVEMBER 1, 2023

For example, we build Nickel with Nix, and we need to make sure the version of wasm-bindgen we pull from Nixpkgs is the same as the one set in Cargo.toml. The actual Nix code to build Nickel calls to a mysterious override function, which is a bespoke mechanism of Nixpkgs to simulate this kind of overriding.

Metadata 113

Metadata Programming Programming Language Coding 113

Cloudera

NOVEMBER 13, 2020

Metadata Caching. This is used to provide very low latency access to table metadata and file locations in order to avoid making expensive remote RPCs to services like the Hive Metastore (HMS) or the HDFS Name Node, which can be busy with JVM garbage collection or handling requests for other high latency batch workloads.

Metadata 143

Metadata Coding SQL Database 143

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 97

Data Governance Government Metadata Datasets 97

Christophe Blefari

JANUARY 20, 2024

Every company out there has his own definition for the data engineer role. The idea behind is to solve data problem by building software. What is data engineering As I said it before data engineering is still a young discipline with many different definitions. Who are the data engineers? Is it really modern?

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Data Engineering Podcast

JULY 24, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

Data Engineer 100

Data Engineer Data Engineering Lambda Architecture Engineering 100

Snowflake

OCTOBER 7, 2024

When scaling data science and ML workloads, organizations frequently encounter challenges in building large, robust production ML pipelines. Define an Entity: Define a Feature View: feature_df is a Snowpark DataFrame object containing your feature definition.

Management 80

Management Building Datasets Government 80

Maxime Beauchemin

JANUARY 20, 2017

Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. It also becomes the role of the data engineering team to be a “center of excellence” through the definitions of standards, best practices and certification processes for data objects.

Data Engineer 130

Data Engineer Data Engineering Engineering ETL Tools 130

Cloudera

AUGUST 16, 2021

Apache Nifi is a powerful tool to build data movement pipelines using a visual flow designer. Ultimately these challenges force NiFi teams to spend a lot of time on managing the cluster infrastructure instead of building new data flows which slows down use case adoption. This will create a JSON file containing the flow metadata.

Cloud 122

Cloud Unstructured Data Utilities Metadata 122

LinkedIn Engineering

APRIL 25, 2023

In this blog post, we will cover how the GraphQL layer is architected for use by our internal engineers to build member and customer facing applications. We had two choices in hand - invest more in Deco to address the pressing issues, or adopt GraphQL and build the necessary infrastructure around it for our needs. Given that our Rest.li

Architecture 109

Architecture Metadata Java Transportation 109

Knowledge Hut

MAY 26, 2024

It houses metadata and both the desired and current state for each resource. So, if any other component needs to access information about the metadata or state of resources stored in the etcd, they have to go through the kube-apiserver. This ensures that all of the configurations are set correctly before being stored in the etcd.

Metadata 52

Metadata Certification Accessible Accessibility 52

Data Engineering Podcast

MAY 18, 2021

In order to eliminate the wasted effort of building custom integrations every time you want to combine lineage information across systems Julien Le Dem introduced the OpenLineage specification. What is the current state of the ecosystem for generating and sharing metadata between systems? What are your goals for the OpenLineage effort?

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

François Nguyen

MARCH 7, 2021

In this article, Juan Sequada gives maybe one of the best definition of Data Mesh ” It is paradigm shift towards a distributed architecture that attempts to find an ideal balance between centralization and decentralization of metadata and data management.”

Government 130

Government Data Governance Data Metadata 130

Data Engineering Podcast

OCTOBER 14, 2018

This is a highly detailed and technical exploration of how a well-engineered metadata layer can improve the speed, accuracy, and utility of large scale, multi-tenant, cloud-native data platforms. How do you handle files on disk that don’t contain all of the fields specified in a table definition?

Data Lake 100

Data Lake Big Data Cloud Hadoop 100

Precisely

OCTOBER 31, 2024

While data products may have different definitions in different organizations, in general it is seen as data entity that contains data and metadata that has been curated for a specific business purpose. A data fabric weaves together different data management tools, metadata, and automation to create a seamless architecture.

Data Architecture 69

Data Architecture Architecture Metadata Government 69

ThoughtSpot

JUNE 28, 2023

Fine-grained personal access token that allows Read access to metadata and Read and Write access to code and commit statuses. Applying analytics-as-code principles, we initially developed a scriptable approach with TML to automate the lifecycle management of analytic content across environments. vcs/git/config/create REST API v2.0

Metadata 97

Metadata Accessible Accessibility Coding 97

Christophe Blefari

JUNE 16, 2023

Metis: building Airbnb’s next generation data management platform — The new manifesto for every data governance company /S. Data graph create an entity diagram from the semantic definition with the API offers you an endpoint to launch pre-aggregations jobs from your scheduler. Telmai raises $5.5m seed round.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

Lyft Engineering

OCTOBER 3, 2023

Data quality is an amorphous term, with various definitions depending on the context. In Verity, we defined data quality as follows: Verity’s Definition of Data Quality The measure of how well data can be used as intended. Five aspects of data quality with the definition in italics and an example in quotes.

Big Data 86

Big Data Metadata Data Warehouse Data 86

Cloudera

AUGUST 24, 2020

When building your data foundation, how can you prioritize innovation within a hybrid cloud strategy? You need to have consistent security and governance that allows you to not only control who has access to data, but also have full insights into lineage, metadata and cataloging throughout your environment.

Cloud 82

Cloud Building Government Data 82

Data Engineering Weekly

JULY 7, 2024

Learn More → Notion: Building and scaling Notion’s data lake Notion writes about scaling the data lake by bringing critical data ingestion operations in-house. link] Jack Vanlightly: Understanding Apache Paimon's Consistency Model Part 1 Table formats are definitely a hot topic in the industry now.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

Marc Lamberti

SEPTEMBER 22, 2023

Digging into the official definition, you will see that Airflow is noted as an open-source platform that programmatically authors, schedules, and monitors workflows. As long as you know Python, you can build data pipelines and fully utilize AIrflow. Airflow stores metadata in it (DAG runs, XComs, Task instances, etc.

Data Pipeline 130

Data Pipeline Python Metadata Database 130

Data Engineering Podcast

JANUARY 7, 2022

In this episode Metaplane founder Kevin Hu shares his working definition of the term and explains the work that he and his team are doing to cut down on the time to adoption for this new set of practices. You can observe your pipelines with built in metadata search and column level lineage. What is your working definition of that term?

BI 100

BI Data Warehouse Metadata SQL 100

Cloudera

MARCH 14, 2023

Key requirements for building data pipelines Every data pipeline starts with a business requirement. Developers who are tasked with building these data pipelines are looking for tooling that: Gives them a development environment on demand without having to maintain it.

Data Pipeline 85

Data Pipeline Designing Kafka Metadata 85

Monte Carlo

AUGUST 25, 2023

A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor. For metadata organization, they often use Hive, Amazon Glue, or Databricks. One advantage of data warehouses is their integrated nature.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Netflix Tech

JULY 22, 2024

A workflow definition is defined in a JSON format. Maestro combines user-supplied fields with those managed by Maestro to form a flexible and powerful orchestration definition. A Maestro workflow definition comprises two main sections: properties and versioned workflow including its metadata.

Machine Learning 103

Machine Learning Coding Data Pipeline Java 103