Marktechpost

JUNE 13, 2024

Data scientists often spend up to 80% of their time on data engineering in data science projects. Objective of Data Engineering: The main goal is to transform raw data into structured data suitable for downstream tasks such as machine learning.

ETL 101

ETL Machine Learning Data Ingestion Big Data 101

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. As previously mentioned, a data fabric is one such architecture.

Data Quality 130

Data Quality Metadata ETL Big Data 130

Pickl AI

OCTOBER 19, 2023

Data Governance Establish data governance policies to define roles, responsibilities, and data ownership within your organization. ETL (Extract, Transform, Load) Processes Enhance ETL processes to ensure data quality checks are performed during data ingestion.

Data Quality 52

Data Quality ETL Machine Learning Data Ingestion 52

Heartbeat

NOVEMBER 6, 2023

Image Source —  Pixel Production Inc In the previous article, you were introduced to the intricacies of data pipelines, including the two major types of existing data pipelines. You also learned how to build an Extract Transform Load (ETL) pipeline and discovered the automation capabilities of Apache Airflow for ETL pipelines.

ETL 52

ETL Python Metadata Deep Learning 52