Tweag

FEBRUARY 22, 2023

I talked about how to write modular and customizable configuration using Nickel’s merging system. Scattering configuration data, schemas and knowledge across many different tools, written in many different languages (HCL, YAML, JSON, TOML, Puppet, Ansible, Helm, etc.) But something is in the air. isn’t sustainable.

Management 52

Management Programming Language Data Schemas Programming 52

Monte Carlo

MARCH 2, 2023

Otherwise you may produce more data anomalies than you prevent. Data Contracts Image courtesy of Andrew Jones. You can think of data contracts as circuit breakers, but for data schemas instead of the data itself. If you are conducting a post mortem, by definition the data anomaly has already occurred.

Food 52

Food Data SQL Data Pipeline 52

Striim

NOVEMBER 8, 2023

The Data Mesh architecture is based on four core principles: scalability, resilience, elasticity, and autonomy. Data mesh technology also employs event-driven architectures and APIs to facilitate the exchange of data between different systems.

Architecture 52

Architecture Generalist Government Datasets 52

Pinterest Engineering

MAY 2, 2023

So our user sequence real-time indexing pipeline is composed of a Flink job that reads the relevant events as they come into our Kafka streams, fetches the desired features for each event from our feature services, and stores the enriched events into our KV store system. The first module retrieves key-value data from the storage system.

Lambda Architecture 65

Lambda Architecture Datasets Software Engineer Software Engineering 65

Cloud Academy

JANUARY 27, 2022

What does a data engineer do – details The architecture that a data engineer will be working on can include many components. The architecture can include relational or non-relational data sources, as well as proprietary systems and processing tools. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Rockset

OCTOBER 6, 2022

Consequently, we needed a data backend with the following characteristics: Scale With ~50 commits per working day (and thus at least 50 pull request updates per day) and each commit running over one million tests, you can imagine the storage/computation required to upload and process all our data.

AWS 52

AWS Data Schemas Accessible Accessibility 52

dbt Developer Hub

FEBRUARY 7, 2022

Tip: If you’re building out a definition like "personal email domains" for the first time, I strongly recommend building alignment upfront with the rest of the business. This is very important for making sure that the domain knowledge is used in the CRM definitions. You most definitely deserve a jaffle. ?

Data Warehouse 52

Data Warehouse Datasets Data SQL 52

Zalando Engineering

SEPTEMBER 28, 2022

Also, it was based on Zalando's "Mosaic" system architecture, which was being phased out in favour of the newer Interface Framework. Interface Framework - To integrate the tool with Zalando's new architecture and design system, to leverage its capabilities and scale with it. However, it had many limitations affecting scalability.

Certification 52

Certification Architecture Data Schemas Metadata 52

Monte Carlo

JANUARY 25, 2023

It can be challenging when a team is expected to take full responsibility for a key data product when there are no guarantees around the upstream data quality. Without clear management of each transformation step stretching back to source systems, teams may be unwilling to bear the responsibility of contracts.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Monte Carlo

APRIL 24, 2023

As we saw in Part 2 of our series , the definition of “building” and “buying” can change based on what layer of the data stack we’re considering. This data ingestion process can be accomplished by either querying the source directly, using upstream systems to publish events, or some combination of the two.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

AltexSoft

OCTOBER 3, 2022

.” Basically, a knowledge graph is obtained in the process of filling ontologies with instances of real data. Due to the fact that every company or even individual creates their own version of knowledge graphs, you won’t find a single standardized definition. Knowledge graphs for organizing data over the internet.

Relational Database 52

Relational Database Banking Media Computer Science 52

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. In this post we will provide details of the NMDB system architecture beginning with the system requirements?—?these key value stores generally allow storing any data under a key).

Media 94

Media Database Metadata Data Schemas 94

Confluent

JUNE 13, 2019

This data pipeline is a great example of a use case for Apache Kafka ®. Observational astronomers study many different types of objects, from asteroids in our own solar system to galaxies that are billions of lightyears away. The technology underlying the ZTF system should be a prototype that reliably scales to LSST needs.

Kafka 102

Kafka Bytes Data Pipeline Python 102

Confluent

MAY 28, 2019

Over time, organizations restructure, project scopes change, and an end system that was used by one application may now be used by multiple applications. If that happens and schema IDs are no longer globally unique, there may be collisions between schema IDs.

Management 83

Management Kafka Java Certification 83

Netflix Tech

OCTOBER 31, 2018

the Media Timeline Data Model In the previous post in this series, we described some important Netflix business needs as well as traits of the media data system?—?called The curious reader might have noticed that a majority of these characteristics relate to properties of the data managed by NMDB.

Media 54

Media Metadata Data MongoDB 54