Mlearning.ai

MAY 16, 2023

It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database. In the extraction phase, the data is collected from various sources and brought into a staging area.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Data Engineering 91

Data Engineering Data Engineer Data Engineering Data Engineering 91

Alation

AUGUST 4, 2022

“Cloud has not replaced big data but lowered the cost of entry,” says Gildersleeve. “Setting up Hadoop on-premises was a huge undertaking. Spark, Tensorflow, Apache Kafka, et cetera, are all out found in cloud databases,” points out Jones. A key challenge of legacy approaches involved data quality.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95