Public Sector

Centralized Approach to Data Quality Increases Visibility into Process Bottlenecks for State Agency 

A modern data vault and enhanced reporting set the stage for a large state agency to increase visibility into data quality issues. This modernization effort created a centralized data repository enabling the organization to be hyper datadriven and establish a data governance program to raise the standard of data quality to improve internal business processes and provide better customer service.  

LET'S BE BRIEF

Challenge

Ongoing data quality issues created bottlenecks in business processes and an overall lack of internal data trust

Objective

Enable stronger data quality through identification and increased visibility into data quality issues to improve business processes. 

Solution

Build a centralized dashboard to monitor data quality issues to enable a proactive approach to resolve data issues negatively impacting the agency. 

THE EXTENDED VERSION

Challenge

The agencys complex financial calculations are dependent upon accurate data figures. Without a comprehensive program to identify issue patterns, underlying problems went unnoticed for long periods of time until they affected crucial processes.  Many data quality issues were identified, but the records of these issues were divided between many systems, making it difficult to accurately scope the organization’s impact, decreasing confidence in the data for business users.  

Solution

The new data vault created a centralized repository enabling our team to create a centralized data quality approachUDig analyzed the agencys data fix logs and interviewed subject matter experts to identify data issues regularly encountered in their work. Working side-by-side with our client, the team conducted targeted data analysis, isolating all instances of these data quality issues into a series of discrete business rules. These rules were used as the basis for an interactive Tableau dashboard, allowing users to track data quality issues over time and target the largest data quality patterns. The visibility afforded by the dashboard enabled the agency to take a proactive approach towards the resolution of these issues and implement fixes before they affected the enduser. This proactive approach to data quality has allowed for increased visibility into process bottlenecks and improved data trust

How We Did It

Dashboard UX/UI Design
Data Strategy & Governance
Exploratory Data Analysis

Tech Stack

  • Tableau 
  • Microsoft SQL Server 
  • SSIS 
  • Python