Features
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 visibility 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 governance 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.
Overcome a major analytics adoption hurdle – lack of trust in the data.
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Features
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.
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| 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 | ||||
| Data Validation and Screening* | ||||
| Report Reliability Badging~ | ||||
| Interface Agreements~ | ||||
| Master Data Management~ |
~Coming Soon
*Server Only Feature