Similarity Analysis

Similarity analysis, one of the metadata analytics capabilities, is used to identify and measure the degree of similarity or resemblance between objects or data points within a dataset.

Orion Governance’s Enterprise Information Governance Graph (EIIG), a self-defined data fabric, offers automated and comprehensive similarity analysis as part of their next generation of metadata management platform. It enables enterprises to effectively enhance their decision-making, increase productivity, and optimize cost.

EIIG’s similarity analysis is based on granular information from a wide range of technology sources including the mainframe, ETL and reporting tools, DBMSs and NoSQL databases, and programming languages such as Python, Java, Scala, and Hive.

With this comprehensive coverage, enterprise customers can quickly discover duplicate or redundant data assets whether they are reports, ETL jobs, or tables regardless how complex their data landscape is.

The whole process of ingesting metadata, cataloging, data lineage visualization, impact analysis, and similarity analysis in an automated workflow within EIIG.

With EIIG, data citizens can perform similarity analysis to easily identify duplicate and redundant information just by clicking data points in a knowledge graph. This is automated self-service without any need to involve IT or a data governance specialist.

What is more, EIIG equips users with the flexibility to choose the level of detail and the type of datasets according to their roles and needs to conduct similarity analysis.

This is possible because EIIG’s similarity analysis is performed in a self-defined data fabric with wide-ranging datasets of all types as well as hierarchical views.

For example, the BI team may focus on just the duplicated reports, the data integration team on redundant ETL jobs, a data engineer on similar tables.

For the risk managers, they may use similarity analysis to detect fraudulent activities by comparing new transactions with historical records and identifying patterns of suspicious similarity.

Compliance officers can use similarity analysis to identify and tag PII datasets to ensure compliance with data privacy regulations.

EIIG’s automated and comprehensive similarity analysis used together with other capabilities such as data catalog, lineage, active metadata, and impact analysis enables enterprises to achieve their desired data-driven outcomes such as better and faster decision-making, cost optimization, and improved productivity.

Faster than any other data lineage feature available

Saves money by reducing total cost of ownership

Requires less time to implement and integrate with current technologies

Support for cloud migration and legacy modernization

Teams are happier using automated tools they can trust

Data lineage experts available to answer questions and troubleshooot

No-code solution open to all team members

Near real-time response provides teams with current information