Data integration is the process of combining data from multiple sources into a unified view to provide users valuable and actionable information. The rapid growth of data sources and volume has made integration essential, especially as businesses seek more and better ways to make sense of and share their enterprise data.
Data integration enables businesses to manage huge datasets from various sources, combining disparate information into a single source of truth. Integration further allows the business to provide users access to the data who can then perform analysis and other processes to uncover actionable insights.
Data integration encompasses the following primary operations, commonly referred to as “extract, load, transform,” or ETL.
Extract, exporting data from specified data sources
Transform, modifying the source data as necessary using rules, merges, lookup tables and other conversion methods to match the destination data
Load, importing the transformed data into a target database
Integrating data via a process of extract, load, and then transform, or ELT, is also common as sophisticated data systems perform transformation following loading, as opposed to before.
Data integration may include a wider range of operations, including:
Data migration or movement and management
Data warehouse automation
As a necessary prerequisite for consolidating data and making it accessible to users, data integration benefits businesses in several ways. To name a few:
Unified, clean, and consistent data across the company (single source of truth)
Improved user access to cross-company data
Faster data preparation and analysis
Reduction in errors and rework
Data Integration vs Ingestion
Data ingestion is the process of adding data to a data repository, such as a data warehouse. Data integration typically includes ingestion but involves additional processes to ensure the accepted data is compatible with the repository and existent data.
Snowflake and Integration
Snowflake's Data Exchange eliminates the long ETL, FTP, and electronic data interchange (EDI) integration cycles often required by traditional data marts. And Snowflake’s comprehensive data integration tools list includes leading vendors such as Informatica, SnapLogic, Stitch, Talend, and many more.