Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Lake Government High Quality Data 81

Monte Carlo

AUGUST 10, 2023

Data lineage provides the answer by telling you which upstream sources and downstream ingestors were impacted, as well as which teams are generating the data and who is accessing it. Data engineering teams needed similar processes and tools to monitor their ETL (or ELT) pipelines and prevent data downtime across their data systems.

Data Pipeline 98

Data Pipeline Software Engineer Software Engineering Machine Learning 98

Lyft Engineering

OCTOBER 3, 2023

High-quality data is necessary for the success of every data-driven company. It is now the norm for tech companies to have a well-developed data platform. This makes it easy for engineers to generate, transform, store, and analyze data at the petabyte scale.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Maxime Beauchemin

JANUARY 20, 2017

They’re highly analytical, and are interested in data visualization. Unlike data scientists — and inspired by our more mature parent, software engineering  — data engineers build tools, infrastructure, frameworks, and services. The data engineer’s focal point is the data warehouse and gravitates around it.

Data Engineering 130

Data Engineering Data Engineer Engineering ETL Tools 130

Netflix Tech

APRIL 26, 2022

ML algorithms can be only as good as the data that we provide to it. This post will focus on the large volume of high-quality data stored in Axion?—?our An example of data about members is the video they had watched or added to their My List. An example of video data is video metadata, like the length of a video.

Metadata 75

Metadata Datasets Machine Learning AWS 75

Monte Carlo

JANUARY 25, 2023

There is, however, an added dimension to this relationship: data producers are often consumers of upstream data sources. Data warehouse producers wear both hats working with upstream producers so they can consume high-quality data and producing high-quality data to provide to their consumers.

Data Warehouse 52

Data Warehouse Data High Quality Data Metadata 52

Monte Carlo

MAY 17, 2023

Luckily, the data observability solution caught what otherwise would have been an otherwise difficult to detect issue. Mitigate Risk of Data Failures Software engineers are also challenged by system and code issues, but data engineers are faced with the unique challenge of issues within the data itself.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52