| Customer information can be conformed to any internal and external data standards an organisation needs. |
Manage Data Structure
The Harmony Series manages the structure of customer data wherever it comes from and whatever its condition. Customer information can be conformed to any internal and external data standards an organisation needs.
The Harmony Series caters for managing data structure through the Harmony Parsing Engine
The Harmony Parsing engine performs six key tasks:
Profiles the data quality dimensions of customer data
Harmony Parsing provides measures of the three primary dimensions of customer data quality.
Comprehensive error analysis
Harmony Parsing contains over 600 error codes that provide a contextual report of all parsing errors, classifying the error and highlighting the data condition where the error occurs. This allows users to group errors by their type and frequency and to plan and execute systematic remediation strategies.
Transforms customer data to any format or predefined standard required
Users can standardise common items in customer data such as name prefixes and street types, to any set of terms required, based on internal or industry standards, or compliance standards such as Post Office accreditation rules.
Identifies and classifies the name entities in complex strings
Bank accounts and insurance policies are often held in joint names. In such cases, Harmony Parsing will automatically parse joint names into separate fields, classify the relationships between them and cross reference them to the original record.
Prepares customer data for Matching
Parsing provides the Harmony Inference Matching engine with high quality data to maximise the likelihood of high confidence matching outcomes.
Prepares customer data for Validation
Harmony’s validation facilities use parsed output to enhance the quality and extend the content of customer records. The parsing process is completed prior to the validation phase to maximise the percentage of records successfully validated or enhanced
Next Steps:
“We have regained confidence in our database. The information is now higher quality, enabling a more accurate targeting of our marketing segments. This will improve our level of customer service and expand our marketing capabilities”
