Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. 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. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Christophe Blefari

MARCH 1, 2023

You can also add metadata on models (in YAML). In a nutshell the dbt journey starts with sources definition on which you will define models that will transform these sources to something else you'll need in your downstream usage of the data. You can read dbt's official definitions.

Data Warehouse 278

Data Warehouse SQL Metadata Raw Data 278

Monte Carlo

JULY 11, 2023

Look for potential biases, flaws, or limitations in the data collection process. Below, we list a few examples: Data entry errors: Mistakes made during the process of entering data into a system can lead to inaccuracies. Accurate data without the necessary context or metadata can be challenging to interpret or use effectively.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

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

Netflix Tech

DECEMBER 3, 2022

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. Workflow Definitions Below you can see a typical file structure of a sample workflow package written in SparkSQL. ???

Data Pipeline 144

Data Pipeline Scala Metadata Food 144

Monte Carlo

AUGUST 30, 2023

But there’s a lot to understand in order to both create the most value from your dbt tests and avoid leaning too heavily on a time-intensive process. Custom data tests are generally run every time a dbt `run` command is executed to process your transformations. And one of the most popular approaches is dbt testing.

SQL 52

SQL Datasets Database High Quality Data 52

AltexSoft

NOVEMBER 23, 2021

The traditional way of data integration involves consolidating disparate data within a single repository — commonly a data warehouse — via the extract, transform, load (ETL) process. If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT.

Process 69

Process Data Lake Metadata Data Warehouse 69

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. The same is true with data. If all the information in a data set is accurate and precise, but key values or tables are missing, your analysis won’t be effective.

Data Collection 40

Data Collection Data Governance Government Data 40

Data Engineering Podcast

FEBRUARY 19, 2023

How does that change based on the type of query/processing engine being used? Acryl]([link] The modern data stack needs a reimagined metadata management platform. Acryl]([link] The modern data stack needs a reimagined metadata management platform. How does that change based on the type of query/processing engine being used?

IT 147

IT Data Lake Metadata Data Warehouse 147

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

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? This is not.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

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. What was your process for determining what subject areas to include in the book? Atlan is the metadata hub for your data ecosystem.

Data Engineering 100

Data Engineering Data Engineer Lambda Architecture Engineering 100

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. number of chunks).

Bytes 99

Bytes Metadata Database Data 99

Data Engineering Podcast

FEBRUARY 26, 2023

In this episode he shares that journey and the combination of technical and organizational challenges that he encountered in the process. What is your philosophy on enforcing uniformity in technical systems vs. relying on interface definitions as the unit of consistency?

Building 147

Building Machine Learning Metadata Data Integration 147

Data Engineering Podcast

SEPTEMBER 11, 2022

Ananth Packildurai created Schemata as a way to make the creation of schema contracts a lightweight process, allowing the dependency chains to be constructed and evolved iteratively and integrating validation of changes into standard delivery systems. Atlan is the metadata hub for your data ecosystem.

Systems 100

Systems Metadata Building MongoDB 100

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

Monte Carlo

OCTOBER 2, 2024

Something’s definitely wrong. Data lineage is the process of tracking data as it moves and evolves throughout its lifecycle, from creation to consumption and eventual deletion. Marquez is a metadata service that implements the OpenLineage API. It’s 9am and you’re rushing to generate a report for your 10 a.m.

Python 52

Python Datasets Metadata Data 52

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. To make this migration easier and as seamless as possible, we will give developers the ability to export their deep-link metadata.”

Metadata 160

Metadata Engineering Building Technology 160

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. A single hospital makes many captures a day, producing terabytes of such data to store and process. Much like Spark, its module ray.data is focused on loading and processing data as scale. width , spec.

Medical 60

Medical Process Cloud Bytes 60

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. Apache Paimon is a relatively low-key format spun out of Flink’s table store.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

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 95

Data Governance Government Metadata Datasets 95

Marc Lamberti

SEPTEMBER 22, 2023

That cake doesn’t get magicked into existence; it involves a process – a step-by-step recipe you carefully need to follow; otherwise, you will get something different. Digging into the official definition, you will see that Airflow is noted as an open-source platform that programmatically authors, schedules, and monitors workflows.

Data Pipeline 130

Data Pipeline Python Metadata Database 130

François Nguyen

JANUARY 18, 2021

In every step,we do not just read, transform and write data, we are also doing that with the metadata. The Dataops Heritage In my previous article, I have described the loop around the devops part of dataops. Last part, it was added the data security and privacy part.

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

LinkedIn Engineering

APRIL 25, 2023

In our previous blog post on GraphQL, we explained how LinkedIn uses GraphQL to expedite the process of onboarding new use-cases for external API partners. entity schemas already go through a review process, a standardized way of federating these Rest.li specifically for GraphQL. Given that our Rest.li Custom lint rules on Rest.li

Architecture 109

Architecture Metadata Java Transportation 109

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. SQL is not very easy to parse.

Data Management 56

Data Management Management Metadata SQL 56

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

JANUARY 23, 2024

Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. The ability of LLMs to process unstructured data is going to change a lot of the foundational table stakes that make up the core of engineering ,” he says. Those who don’t embrace it will be left behind.

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Data Engineering Podcast

MAY 22, 2022

What is the process for setting up a Flyte deployment? What are the patterns that you and the community have established to encourage discovery and reuse of granular task definitions? Data orchestration engines are a natural point for generating and taking advantage of rich metadata.

Machine Learning 130

Machine Learning Data Engineering Data Engineer Cloud 130

Airbnb Tech

NOVEMBER 28, 2023

To meet this challenge, we introduced the “Midas” process to certify our data. Starting in 2020, the Midas process, along with the work to re-architect our most critical data models, has brought a dramatic increase in data quality and timeliness to Airbnb’s most critical data. Align on the input components for assessing data quality.

Data Warehouse 98

Data Warehouse Metadata Data Certification 98

Knowledge Hut

MARCH 7, 2024

Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques. The greatest data processing challenge of 2024 is the lack of qualified data scientists with the skill set and expertise to handle this gigantic volume of data.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Ascend.io

APRIL 22, 2024

A unified platform that combines a powerful metadata core, an extensible plugin architecture, DataAware automation, and multiple AI Assistants. Lack of unified metadata makes it difficult to optimize pipelines, avoid redundant processing, and quantify data engineering costs.

Project 52

Project Metadata Data Pipeline Data Engineering 52

phData: Data Engineering

NOVEMBER 1, 2024

VP of Architecture, Healthcare Industry Organizations will focus more on metadata tagging of existing and new content in the coming years. Get the Trendbook Data Governance Maturity For many organizations, data governance is still in the early stages, focusing on defining policies and processes. No problem! is fairly advanced.

Government 52

Government Data Governance Finance Metadata 52

Zalando Engineering

OCTOBER 18, 2023

The query directives are generally useful for clients to express certain types of metadata for the query. This process is cumbersome, but it is on purpose. on FIELD_DEFINITION For example, it is used in a query definition as follows - type CustomerConsent { status : String ! We will discuss this in detail in the next section.

Metadata 82

Metadata Coding Banking Designing 82

Cloudera

MARCH 14, 2023

Allows them to iteratively develop processing logic and test with as little overhead as possible. Plays nice with existing CI/CD processes to promote a data pipeline to production. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Data Pipeline 82

Data Pipeline Designing Kafka Metadata 82

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. vcs/git/config/create REST API v2.0

Metadata 97

Metadata Accessible Accessibility Coding 97

Towards Data Science

MAY 7, 2024

Now you have to decide what sorts of things to test in order to figure out definitively if the tool is the right commitment for you and the team. This will help create an overall picture of logging, metadata, latency, CDC, and all the other things that come with a pipeline. Gather the team together and determine what these things are.

ETL Tools 79

ETL Tools Metadata Data Integration Data Science 79

DoorDash Engineering

DECEMBER 5, 2023

Almost six billion messages are processed each day at an average rate of four million messages per minute, which sometimes peaks at double that rate. The slowest step in that process was provisioning Kafka Topics, which involved on-call engineer approval and was prone to failure, further increasing the on-call load.

Kafka 91

Kafka Programming Language Metadata Architecture 91