Data Quality Analysis & Repairs

ICT Revolutions can carry out a full landscape analysis at the beginning of a replacement case management system implementation. We do this in partnership with the customer’s Key Data Stakeholder(s). The process establishes the location, structure and quality of the source data. 

There are 4 key tasks in any data discovery project.

1. Customer provides initial statement of requirements
2. Landscape analysis
3. Project decomposition
4. Establish Data Task Group

The output from a data discovery phase is the creation of the first drafts of five key project documents:

• Legacy Data Store Register
• Key Data Stakeholder Register
• Migration Sign-off Requirements
• Migration Issues Log
• Data Migration Strategy

From this, a model of the data structures that will need to be extracted is formed, together with baseline rules that should be applied during the extract. The data quality of each data store is also baselined at this stage.

Landscape Analysis

We begin any data migration project with a landscape analysis and scope as this determines which legacy systems and data stores are required for the migration. A review of all edge systems, including ad-hoc databases and spreadsheets, etc., must take place to determine the source of the truth of all data within scope of the migration. It should be done quickly, and all systems scoped and agreed accordingly.

Migration Scope

A baseline scope concerning the breadth of client, casework and person data including related people along with the depth of historic data must be established at the beginning of the project and signed off with the business. It should also detail items that are out of scope and must be open to amendment during the migration. Issues of historic data quality are often the trigger for such amendments.

What are the benefits?

The importance of good quality data will be embedded among the users at all stages of the implementation process, from user and data testing through to the training programme.

The data discovery phase of any project is designed to prepare for the smooth delivery of data migration projects later on in a replacement systems implementation.

Another benefit to our data discovery process is that knowledge gained from a data discovery phase can help define requirements in the tender process.