Data quality for government agencies
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How bad data affects public sector data?
Inter-agency matching limits data reliability
Repeated copies of the same entity increase the complexity in creating a holistic view of a specific population segment.
High false negatives
Inaccurate record linkage processes can fail to detect fuzzy, phonetic mis-keyed and abbreviated variations resulting in fewer matches.
Long cycle times
Duplicate and redundant records cause a surge in data bandwidth, increasing the time taken to process records.
Unreliable planning data
Compromised research integrity due to inaccurate public data can hinder efficient allocation of public policy resources and funds.
Lack of unique identifiers
Tracking individuals using unique identifiers across multiple agency databases whilst protecting PII data is a challenge.
Mismanagement of public funds
Poor visibility into financial and accounting data can cause overpayments to contractors and delayed collections from debtors.
DataMatch Enterprise – A robust cross-jurisdictional matching solution
See what our clients are saying...
The idea of linking two groups of records was overwhelming for the research department. The process would be very time-consuming and threaten the timeliness and process of the research activitie'
DataMatch Enterprise™ was much easier to use than the other solutions we looked at. Being able to automate data cleaning and matching has saved us hundreds of person-hours each year.
It scales our time very well, I can’t quantify in dollar terms since it’s new, but I would say that it represents thousands of dollars since it’s time that is not being spent by our employees.