Precisely

OCTOBER 31, 2024

With data volumes skyrocketing, and complexities increasing in variety and platforms, traditional centralized data management systems often struggle to keep up. 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

Monte Carlo

JULY 11, 2023

Examples of inaccurate data Inaccurate data can arise in a few different ways, all primarily due to manual errors, system hiccups, code changes, or data pipeline breakages. Below, we list a few examples: Data entry errors: Mistakes made during the process of entering data into a system can lead to inaccuracies.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Monte Carlo

AUGUST 30, 2023

Often, teams run custom data tests as part of a deployment pipeline, or scheduled on production systems via job schedulers like Apache Airflow, dbt Cloud, or via in-built schedulers in your data warehouse solution. With dbt tests, no news is good news. Common dbt testing use cases Time to make all these how-to instructions come to life.

SQL 52

SQL Datasets Database High Quality Data 52

Tweag

NOVEMBER 1, 2023

The last important remaining piece to explore is the merge system. In this post, we’ll see how to use the Nickel merge system to write reusable configuration modules, and why the merge approach seems to be more adapted for modular configurations than plain functions, despite Nickel being a functional language. s t r i n g.

Metadata 114

Metadata Programming Programming Language Coding 114

Data Engineering Podcast

NOVEMBER 6, 2022

He also describes the considerations involved in bringing behavioral data into your systems, and the ways that he and the rest of the Snowplow team are working to make that an easy addition to your platforms. Atlan is the metadata hub for your data ecosystem. What are some of the unique characteristics of that information?

Building 130

Building IT Metadata MongoDB 130

Netflix Tech

DECEMBER 3, 2022

Thanks to the Netflix internal lineage system (built by Girish Lingappa ) Dataflow migration can then help you identify downstream usage of the table in question. Workflow Definitions Below you can see a typical file structure of a sample workflow package written in SparkSQL. ??? backfill.sch.yaml ??? daily.sch.yaml ???

Data Pipeline 144

Data Pipeline Scala Metadata Food 144

Tweag

MAY 16, 2023

That’s a dangerous mistake: with the advent of IaC for the cloud, configuration has become an important aspect of modern software systems, and a critical point of failure. A REPL nickel repl , a markdown documentation generator nickel doc and a nickel query command to retrieve metadata, types and contracts from code.

MySQL 135

MySQL Metadata Data Validation Coding 135

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 85

Big Data Metadata Data Warehouse Data 85

Data Engineering Podcast

JULY 24, 2022

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. How have the definitions shifted over the past few decades? Atlan is the metadata hub for your data ecosystem.

Data Engineer 100

Data Engineer Data Engineering Lambda Architecture Engineering 100

Monte Carlo

OCTOBER 2, 2024

Something’s definitely wrong. But as you begin to scroll through your emails, you spot a message from IT that you brushed off last week: The data lineage system is finalized and ready for use. Marquez is a metadata service that implements the OpenLineage API. But as you scan the numbers, something feels… off.

Python 52

Python Datasets Metadata Data 52

Data Engineering Podcast

FEBRUARY 26, 2023

What are the technical systems that you are relying on to power the different data domains? What is your philosophy on enforcing uniformity in technical systems vs. relying on interface definitions as the unit of consistency? What are the technical systems that you are relying on to power the different data domains?

Building 147

Building Machine Learning Metadata Data Integration 147

Netflix Tech

SEPTEMBER 18, 2024

message Item ( Bytes key, Bytes value, Metadata metadata, Integer chunk ) Database Agnostic Abstraction The KV abstraction is designed to hide the implementation details of the underlying database, offering a consistent interface to application developers regardless of the optimal storage system for that use case.

Bytes 99

Bytes Metadata Database Data 99

Monte Carlo

JULY 10, 2023

That’s where the definition of data completeness comes in. Data profiling Data profiling uses a tool or programming language to surface metadata about your data. This can lead to data that’s incomplete in one system, even if it’s present in another. The same is true with data.

Data Collection 40

Data Collection Data Governance Government Data 40

Data Engineering Weekly

JULY 7, 2024

[link] Jack Vanlightly: Understanding Apache Paimon's Consistency Model Part 1 Table formats are definitely a hot topic in the industry now. The author highlights Paimon’s consistency model by examining the metadata model. Canva writes about the evolution of experimentation system design and the current state of the function.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

Data Engineering Podcast

MARCH 27, 2022

You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms. What is your working definition of "data governance" and how does that influence your product focus and priorities?

Data Governance 130

Data Governance Government Cloud Building 130

Christophe Blefari

JANUARY 20, 2024

Every company out there has his own definition for the data engineer role. What is data engineering As I said it before data engineering is still a young discipline with many different definitions. Reddit r/dataengineering wiki a place where some data eng definitions are written. Who are the data engineers? Is it really modern?

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Pinterest Engineering

OCTOBER 2, 2024

Catalog/Metadata Management , which is responsible for storing and serving table metadata, including ownership, schemas, SLAs, etc., and also providing runtime metadata about the platform Security and Auditability , which ensures GDPR compliance, advanced levels of auditability, security, AAA, etc.

Data Management 56

Data Management Management Metadata SQL 56

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. For example, a single table named ‘Customers’ is actually an aggregation of metadata that manages and references several data files, ensuring that the table behaves as a cohesive unit.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 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 102

Machine Learning Coding Data Pipeline Java 102

Monte Carlo

MARCH 4, 2024

Table of Contents How Data Observability Works Made For The Lakehouse: Iceberg and Delta Transform in place: Dynamic Tables and Delta Live Tables Why This Matters How Data Observability Works Data observability provides full visibility into your data, systems, and code so you can find and fix bad data quickly.

Metadata 52

Metadata Data Lake Data Engineer Data Engineering 52

LinkedIn Engineering

APRIL 25, 2023

Here are some of the primary differences compared to the widely used architecture in the industry: The GraphQL type system used at LinkedIn is completely autogenerated. Type System Generator The GraphQL type system used at LinkedIn is autogenerated by federating individual entity schemas from the Rest.li Given that our Rest.li

Architecture 109

Architecture Metadata Java Transportation 109

Cloudera

MARCH 9, 2021

While Cloudera Data Platform (CDP) already supports the entire data lifecycle from ‘Edge to AI’, we at Cloudera are fully aware that enterprises have more systems outside of CDP. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 96

Data Governance Government Metadata Datasets 96

Zalando Engineering

OCTOBER 18, 2023

The query directives are generally useful for clients to express certain types of metadata for the query. The type system directives are available for the locations listed below. on FIELD_DEFINITION For example, it is used in a query definition as follows - type CustomerConsent { status : String ! are some entities.

Metadata 82

Metadata Coding Banking Designing 82

phData: Data Engineering

NOVEMBER 1, 2024

Strong data governance also lays the foundation for better model performance, cost efficiency, and improved data quality, which directly contributes to regulatory compliance and more secure AI systems. VP of Architecture, Healthcare Industry Organizations will focus more on metadata tagging of existing and new content in the coming years.

Government 52

Government Data Governance Finance Metadata 52

Data Engineering Podcast

MAY 22, 2022

Get started with Kyligence today at dataengineeringpodcast.com/kyligence Your host is Tobias Macey and today I’m interviewing Ketan Umare and Haytham Abuelfutuh about Flyte, the open source and kubernetes-native orchestration engine for your data systems Interview Introduction How did you get involved in the area of data management?

Machine Learning 130

Machine Learning Data Engineer Data Engineering Cloud 130

Data Engineering Podcast

MAY 18, 2021

Summary Data lineage is the common thread that ties together all of your data pipelines, workflows, and systems. 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.

Metadata 100

Metadata Kafka Data Warehouse Hadoop 100

Ascend.io

APRIL 22, 2024

A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants. As data pipelines sprawl across disparate systems, it becomes harder to trace data lineage, track data quality, and quickly pinpoint issues when they arise.

Project 52

Project Metadata Data Pipeline Data Engineer 52

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

Knowledge Hut

MARCH 7, 2024

Syncing Across Data Sources Once you import data into Big Data platforms you may also realize that data copies migrated from a wide range of sources on different rates and schedules can rapidly get out of the synchronization with the originating system. Two, it creates a commonality of data definitions, concepts, metadata and the like.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

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

Airbnb Tech

NOVEMBER 28, 2023

We identified the following objectives for the score: Evolve our understanding of data quality beyond a simple binary definition (certified vs uncertified). Luckily, we had two existing tools that would make this much easier: Dataportal (Airbnb’s data catalog and exploration UI), and the Unified Metadata Service (UMS).

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Booking.com Engineering

NOVEMBER 11, 2024

To address this, we integrated a recommendation pipeline into the core of our system. Enrich: Adds value with localized content, images, metadata and other enrichments. The diagram above illustrates how features integrate with models, highlighting the flexibility we’ve incorporated into the system for feature reuse.

Machine Learning 58

Machine Learning Utilities Metadata Systems 58

Christophe Blefari

FEBRUARY 3, 2023

Lyft, powering millions of real-time decisions with LyftLearn Serving — Architecture of the decentralized system Lyft use to deploy and serve ml models. What's often stays is that AE is between DE and DA, so the definition is often done complementarily to other positions. In the end actually, the answer depends.

BI 130

BI Google Cloud Machine Learning SQL 130

Netflix Tech

JANUARY 10, 2024

Since then, the video pipeline has undergone substantial improvements and broad expansions: Starting with Standard Dynamic Range (SDR) at Standard-Definitions , we expanded the encoding pipeline to 4K and High Dynamic Range (HDR) which enabled support for our premium offering. This introductory blog focuses on an overview of our journey.

Process 93

Process Pipeline-centric Media Metadata 93

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. Starting with just a few tasks to thousands of tasks thanks to the support of various systems such as Dasks, Kubernetes, or Celery. ” What is Apache Airflow?

Data Pipeline 130

Data Pipeline Python Metadata Database 130

Snowflake

SEPTEMBER 24, 2024

Some of the most pressing risks include: Privacy: AI systems can process enormous amounts of personal data, raising concerns about how this data is used and protected. Autonomy: AI systems used in decision-making processes can potentially undermine individual autonomy if not properly designed.

Government 72

Government Algorithm Machine Learning Metadata 72

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. This is a great exploration of what it means to treat your data platform as a living system and apply state of the art engineering to it.

BI 100

BI Data Warehouse Metadata SQL 100