Background

A large civil defense organization managed their operational data in nine vertical applications.  The content of each system’s data overlapped to a degree with one another, resulting in redundant and often incomplete data.

Problem

A new transactional (OLTP) system was designed to encompass and enhance the functionality of the nine legacy systems.  The problem was determining how to cleanse and merge the data from the nine disparate systems.

Solution

We recently designed an ETL tool to manage the business rules that govern the sharing of information between systems.  We utilized this tool to reverse engineer the table definitions and map the source tables and columns to the target tables and columns. 

We conducted a Data Quality Analysis (DQA) to identify data that required manual correction.  Doing so allowed us to pre-cleanse the data so that we could automate the entire production load.  Since the target system was replacing the nine source systems, load performance wasn’t a significant issue.  The migration would be run once during the production launch of the replacement system.

Benefits

Created a Single, Unified Information Repository for all Aspects of Fleet Logistics

Saved the nearly $200k cost of ETL Software and Related Implementation Costs

Elimination of Redundant Data Entry into the Nine Disparate Systems

Improved Data Quality Controls