Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices.

Big Data 73

Big Data Data Data Storage SQL 73

Monte Carlo

JANUARY 25, 2023

The contracts themselves should be created using well-established protocols for serializing and deserializing structured data such as Google’s Protocol Buffers (protobuf), Apache Avro, or even JSON. We can specify the fields of the contract in addition to metadata like ownership, SLA, and where the table is located.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 52

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94

Media Database Metadata Data Schemas 94

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

Towards Data Science

FEBRUARY 15, 2023

Before going into further details on Delta Lake, we need to remember the concept of Data Lake, so let’s travel through some history. Delta Lake also refuses writes with wrongly formatted data (schema enforcement) and allows for schema evolution. show() The history object is a Spark Data Frame.

Data Lake 80

Data Lake Data Warehouse Hadoop Data Architecture 80

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 97

Data Warehouse Datasets Data Big Data 97