Data quality for government agencies

Enhance inter-agency matching by identifying missed records across multiple databases while safeguarding PII. Ensure regulatory compliance and program performance with confidence.

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How bad data affects public sector data?

70%

Inter-agency matching limits data reliability

7 out of 10 government officials state that bad data quality disrupts their ability to run the public’s business.
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Duplicate records

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 may fail to detect fuzzy, phonetic, mis-keyed, or abbreviated variations, resulting in fewer matches.

Long cycle times

Duplicate and redundant records increase data bandwidth usage, slowing down record processing.

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 across multiple agency databases using unique identifiers, while protecting PII, remains a challenge.

Mismanagement of public funds

Limited visibility into financial and accounting data can lead to overpayments to contractors and delays in collecting from debtors.

Solution

DataMatch Enterprise – A robust cross-jurisdictional matching solution

DataMatch Enterprise is Data Ladder’s flagship software solution, enabling public sector and federal agencies to accurately link records across multiple states and territories. Using proprietary fuzzy logic algorithms and real-time API workflows, DataMatch Enterprise can identify golden records in days rather than months.

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Customer Stories

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'

West Virginia University

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.

Shelley HahnBusiness Development, St. John Associates
Shelley Hahn

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.

Monitoring and Reporting Director, A Global Private Market Firm

Business Benefits

What’s in it for you?

Better regulatory compliance

Ensure accuracy and consistency in data reporting by standardizing formats, naming conventions, and patterns for compliance.

Keep track of anomalies

Conduct routine database audits using data profiling to identify spelling, punctuation, casing errors, and null values.

Uncover missing matches

Detect fuzzy, phonetic, mis-keyed, and abbreviated variations to achieve higher cross-jurisdictional match rates across multiple states and territories.

Enhance inter-agency matching

Establish master IDs to connect individuals across multiple agency databases without compromising PII.

Expedite request management

Automate record linkage and cleansing using real-time API flows or batch schedules to accelerate processing.

Effective policy planning

Maintain reporting and data integrity to support public policy decisions, including fund appropriation and resource allocation.

Why Data ladder

Want to know more?

Check out DME resources

Merging Data from Multiple Sources – Challenges and Solutions

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