Cloudera

FEBRUARY 9, 2021

Ingesting into cloud storage directly is independent of any data warehouse compute services, which resolves a common issue in the traditional data warehouse that ETL jobs and analysis queries very often compete against each other for resources. The history data is always required for certain industry regulatory compliance.

Data Warehouse 67

Data Warehouse Cloud Kafka Cloud Storage 67

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

ProjectPro

FEBRUARY 8, 2023

Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98

AWS Scala Metadata Data Lake 98

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

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

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. Tools like dbt have also debuted semantic layer features to much fanfare.

Food 52

Food Data SQL Data Pipeline 52