Governance and Quality

One of the key challenges in analytics today is to co-ordinate between different stakeholders' needs for self service and to encourage better data stewardship practices.

Quality Control

Automate data quality checks including reconciliation and detection of duplicate records.

Data Acquisition

Provide visbility of data availability and automatically alert processing issues.

Publishing Control

Create mandatory metadata to capture before reports are published. Classify documents and reports for easier discovery.

Role Based Security

Assign responsibility to data stewards and report authors across departments and regions.

Data Stewardship

Enforce data gonvernance policies such as classifying data sensitivity and capturing descriptions of key metrics.

Business Glossary

Deliver better context of reports with an integrated report and data catalog.


How Loome does it

Loome consists of a number of modules, each aimed at augmenting a specific part of your enterprise data governance and quality practice.

Get Started Now
Module Integrate Assist Monitor Publish
Data Catalogue and Business Glossary
Automated Reconciliation
Single Customer View Processing
Data Job Instrumentation
Audience Targeted Report Portal
Report Publishing Process
Report Issues Help Desk
SME Tagging
Report Usage
Federate Content Management
Technical Data Lineage*
Data Validation and Screening*
Report Reliability Badging*
Interface Agreements*
Master Data Management*

*coming soon

Want to find out more? Contact us for any information you need.