Data Consolidation, Data Warehouse, ETL Tools and Structured Data

Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

DECEMBER 7, 2021

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. What is a Big Data Pipeline?

Data Pipeline

Data Pipeline Architecture Kafka AWS

Data Warehousing Guide: Fundamentals & Key Concepts

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse

Data Warehouse Unstructured Data AWS Business Intelligence

Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

AltexSoft

SEPTEMBER 10, 2021

What is data integration and why is it important? Data integration is the process of taking data from multiple disparate internal and external sources and putting it in a single location (e.g., data warehouse ) to achieve a unified view of collected data. Key types of data integration.

Data Integration

Data Integration Data Consolidation Data Warehouse BI

Data Engineering Digest

Data Pipeline- Definition, Architecture, Examples, and Use Cases

Data Warehousing Guide: Fundamentals & Key Concepts

Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

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