AltexSoft

OCTOBER 3, 2022

While DBpedia uses Wikipedia data to enrich the graph, the Wikidata graph developed and launched in 2012 is designed to store knowledge that will be used already in Wikipedia (mostly for filling infoboxes and tables on the page) in many available languages. General scenarios of using knowledge graphs.

Relational Database 52

Relational Database Banking Media Pharmaceutical 52

dbt Developer Hub

NOVEMBER 28, 2021

This could just as easily have been Snowflake or Redshift, but I chose BigQuery because one of my data sources is already there as a public dataset. dbt seeds data from offline sources and performs necessary transformations on data after it's been loaded into BigQuery. I spun up an instance using its docker/up.sh

Raw Data 52

Raw Data Metadata Datasets Database 52

Netflix Tech

OCTOBER 27, 2020

For example, in order to enhance our user experience, one online application fetches subscribers’ preferences data to recommend movies and TV shows. The data warehouse is not designed to serve point requests from microservices with low latency. Personalized articles in Netflix Help Center powered by Bulldozer.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Netflix Tech

OCTOBER 31, 2018

The Media Document Model The Media Document model is intended to be a flexible framework that can be used to represent static as well as dynamic (varying with time and space) metadata for various media modalities. Timing Model We use the Media Document model to represent timed metadata for our media assets.

Media 54

Media Metadata Data MongoDB 54

Zalando Engineering

SEPTEMBER 28, 2022

In this post, George and Daniel describe the product that was built to serve this purpose - its problem space, the solution design process, the technological context and how the product evolved to include new use-cases, such as the Zalando Sustainability topic. It has basic fields like the page title, the URL path and SEO related metadata.

Certification 52

Certification Architecture Data Schemas Metadata 52

Ascend.io

MAY 19, 2023

The holistic approach of the post-modern data stack translates into numerous benefits: First, it accelerates pinpointing and troubleshooting pipeline hotspots with a single console that observes the entire data pipeline and all its processes. Second, it enhances governance and security.

Data Pipeline 52

Data Pipeline Data Engineering Data Engineer Media 52

Zalando Engineering

SEPTEMBER 8, 2021

Feels like Zalando - We want a consistent and accessible look and feel for all user journeys and ability to experiment with design fast, across multiple user flows. We want to avoid unwanted data coupling and allow Renderers to be reused in other contexts with minimal risks. The page rendering always starts with an Entity.

Engineering 52

Engineering Computer Science Data Schemas Coding 52

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 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. Hive stores the metadata in RDBMS rather than HDFS.

Hadoop 40

Hadoop Metadata SQL Database 40

Confluent

APRIL 30, 2019

However, as a programming interface, such a tedious development cycle should not be the design philosophy of the Streams DSL. For this specific case, when the StreamBuilder#build() method is called, Streams will “push up” the repartitioning phase of the logical plan based on the captured metadata before compiling it to the processor topology.

Kafka 90

Kafka Coding Process Bytes 90

Towards Data Science

NOVEMBER 4, 2023

Back in October, I wrote about the rise of the Data Engineer, the role, its challenges, responsibilities, daily routine and how to become successful in this field. The data engineering landscape is constantly changing but major trends seem to remain the same. So here are a few things to consider that can help us answer these questions.

Data Engineering 89

Data Engineering Data Engineer Engineering BI 89