AltexSoft

OCTOBER 3, 2022

The logical basis of RDF is extended by related standards RDFS (RDF Schema) and OWL (Web Ontology Language). They allow for representing various types of data and content (data schema, taxonomies, vocabularies, and metadata) and making them understandable for computing systems.

Relational Database 52

Relational Database Banking Media Computer Science 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 Database Datasets 52

Cloudera

FEBRUARY 9, 2021

Schema Management. Avro format messages are stored in Kafka for better performance and schema evolution. Cloudera Schema Registry is designed to store and manage data schemas across services. NiFi data flows can refer to the schemas in the Registry instead of hard coding. . > Minutes.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

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

Netflix Tech

OCTOBER 27, 2020

As the paved path for moving data to key-value stores, Bulldozer provides a scalable and efficient no-code solution. Users only need to specify the data source and the destination cluster information in a YAML file. Bulldozer provides the functionality to auto-generate the data schema which is defined in a protobuf file.

Data Warehouse 99

Data Warehouse Datasets Data Big Data 99

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. Change Enablement In the world of data, change is as inevitable as the rising sun.

Data Pipeline 52

Data Pipeline Data Engineer Data Engineering Media 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.

Food 52

Food Data SQL Data Pipeline 52

Monte Carlo

JANUARY 25, 2023

All of these options allow you to define the schema of the contract, describe the data, and store relevant metadata like semantics, ownership, and constraints. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located. Consistency in your tech stack.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Towards Data Science

JANUARY 17, 2024

spark.sql.catalog.spark_catalog: Sets the Spark catalog to Delta Lake’s catalog, allowing table management and metadata operations to be handled by Delta Lake. One of its neat features is the ability to store data in a compressed format, with snappy compression being the go-to choice.

Big Data 68

Big Data Data Data Storage SQL 68

Towards Data Science

FEBRUARY 15, 2023

Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution. It contains a detailed description of each operation performed, including all the metadata about the operation. show() The history object is a Spark Data Frame. delta_table.history().select("version",

Data Lake 75

Data Lake Data Warehouse Hadoop Architecture 75

Zalando Engineering

SEPTEMBER 28, 2022

System architecture context relevant for the Landing Page stack Content Data Model The actual content of a landing page is managed within Contentful as "entries"; each entry-type having its own data schema definition, validation rules and a content-upload UI for the content editors. The main entry is the landing page itself.

Certification 52

Certification Architecture Data Schemas Metadata 52

ProjectPro

JANUARY 31, 2023

Why is HDFS only suitable for large data sets and not the correct tool for many small files? NameNode is often given a large space to contain metadata for large-scale files. The metadata should come from a single file for optimal space use and economic benefit. And storing these metadata in RAM will become problematic.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Zalando Engineering

SEPTEMBER 8, 2021

We want to avoid unwanted data coupling and allow Renderers to be reused in other contexts with minimal risks. Renderers have access to Zalando’s GraphQL Mutation APIs which allows remote data to be modified. Rendering Engine Rendering Engine is the framework powering the Renderers. The page rendering always starts with an Entity.

Engineering 52

Engineering Computer Science Coding Data Schemas 52

phData: Data Engineering

SEPTEMBER 27, 2024

A data catalog is a detailed inventory of all the customer data assets within your organization, including datasets, databases, APIs, and even reports and dashboards. It’s like having a detailed card catalog for your customer data library. Those days are gone!

Data 52

Data Raw Data Data Lake Architecture 52

Confluent

APRIL 30, 2019

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. With the topology optimization framework added to the Streams DSL layer in Kafka 2.1,

Kafka 91

Kafka Coding Process Bytes 91

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

ProjectPro

NOVEMBER 22, 2021

The StructType and StructField classes in PySpark are used to define the schema to the DataFrame and create complex columns such as nested struct, array, and map columns. StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. appName('ProjectPro').getOrCreate()

Hadoop 52

Hadoop Python Datasets Metadata 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

Towards Data Science

NOVEMBER 4, 2023

What I like about it is that it makes it really easy to work with various data file formats, i.e. SQL, XML, XLS, CSV and JSON. Among other benefits, I like that it works well with semi-complex data schemas. Pandas is an absolute beast in the world of data and there is no need to cover it’s capabilities in this story. .")

Data Engineer 80

Data Engineer Data Engineering Engineering BI 80

Cloudera

JANUARY 11, 2021

In addition, it can be challenging to keep a strong control of costs and to know where your data resides in an effort to serve your business well. Shared Data Experience (SDX), a shared persistent layer of access models, lineage-audit trace, and all metadata, is the key to the Cloudera data lake implementation.

Data Warehouse 63

Data Warehouse Pharmaceutical Data Lake BI 63

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. A few tips for a safe migration using data lineage: Document current data schema and lineage. Analyze your current schema and lineage.

Data Warehouse 52

Data Warehouse BI Data Government 52