AWS Machine Learning Blog

JANUARY 6, 2023

TR has a wealth of data that could be used for personalization that has been collected from customer interactions and stored within a centralized data warehouse. The user interactions data from various sources is persisted in their data warehouse. The following diagram illustrates the ML training pipeline.

AWS 66

AWS Data Warehouse ML ML 66

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Credits can be purchased for 14 cents per minute.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Mlearning.ai

MAY 16, 2023

This article discusses five commonly used architectural design patterns in data engineering and their use cases. ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. Finally, the transformed data is loaded into the target system.

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