Google Cloud Data Fusion for Better Data Accessibility
Google Cloud Data Fusion is a fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT ( Extract Transform and load /Extract load Transform) data pipelines efficiently without any hassle.
Google Cloud Data Fusion is a fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT (Extract Transform and load/Extract load Transform) data pipelines efficiently without any hassle.
Smarter data integration for smarter analytics :
Google Cloud Data Fusion completely managed cloud-native data integration service that helps users efficiently to build and manage ETL/ELT( Extract Transform and load /Extract load Transform) data pipelines.
With a user-friendly graphical interface (GUI) and a broad open-source library of preconfigured connectors and transformations, Google Cloud Data Fusion moves an organization’s focus away from code and integration towards insights and action.
Complete Code-free deployment of data pipelines:
Google Cloud Data Fusion gives a visual point-and-click interface (Easy to access interface) that enables the complete code-free development of ETL(Extract Transform and load) pipelines. When users combined with its broad library of data transformation blueprints, Google Cloud Data Fusion authorize a self-service model of data integration that removes the expertise-based bottlenecks and accelerates time to insight.
An open core, delivering hybrid and multi-cloud integration:
Google Cloud Data Fusion is created on the open-source project CDAP(Cask Data Application Platform) and this open core ensures the data pipeline portability for users. Cask Data Application Platform (CDAP)’s broad integration with on-premises and public cloud platforms give Google Cloud Data Fusion users the ability to break down and deliver insights that were previously inaccessible.
Robust data engineering through collaboration and standardization:
Google Cloud Data Fusion offers preconfigured transformations from an OSS (Operational Support System) library as well as the ability to create an internal library where you can customize the connections and transformations that can be shared, validated, and reused across an organization. It lays the foundation for collaborative data engineering as well as improves the overall productivity of an organization. That means less waiting for data engineers and, most importantly, less sweating about code quality.
Get more from Google’s industry-leading big data tools:
Google Cloud Data Fusion simplifies data security and ensures that your data is frequently available for analysis. Whether you’re curating a data lake with Cloud Storage and Cloud Dataproc, moving data into BigQuery for data warehousing, or transforming data to land it in a relational store like Cloud Spanner, Cloud Data Fusion’s integration makes development and iteration fast as well as easy.