Data Dictionary Creation (4 of 5)

Although the Data Dictionary was the tactical focus of the engagement described in the previous blogs, we gave it a back seat to the Culture and Data Governance activities … believing those to be foundational in order to make the Data Dictionary a viable tool.

The organization had more than 40 different apps or databases that contained redundant data that has not been correlated.  Our challenge was to develop a process and a format for identifying and capturing the correlations among and between those redundant data elements, the Data Dictionary being the result. Our approach was to involve the organization’s resources in the process, and to limit our scope to the three most significant systems:

1.     Constituent Information

2.     Contact Relationship Management

3.     Human Resources (Insurance Benefits & Payroll)

The goal was to enable the organization’s resources to continue the process for the remaining systems after our departure. While this effort was under way, they were in the process of evaluating replacement or consolidation solutions for Constituent and HR, but there was really nothing sacred at this point.

After reviewing each of the systems, we compiled key fields, descriptions, data types, and validation rules into a single multi-tab spreadsheet for strategic alignment. Acquiring adequate documentation for two of the systems proved to be a challenge.

After analyzing the data elements of the three source systems, we compiled a list of the unique constituent-related attributes that appeared in one or more of the systems. Working with the organization’s team, we identified Harmonized Names for all of the attributes, established data types and validation rules for them, and started the process of mapping them to the corresponding attributes in each of the source systems.

As an aid to understanding their data structures, we developed entity relationship diagrams for two of the source systems based on documentation provided. We also generated a diagram representing the recommended data structure of their standardized constituent dataset.

Overall, the Data Dictionary documented the mission-critical data attributes that are maintained across the entire application landscape. In the absence of either MDM or a strategic middleware strategy, the Data Dictionary will function as the rulebook that will govern the migration of data from the various applications into the Data Warehouse. Critical decisions regarding common identifiers, data rationalization, and transformation rules will be based on the contents of the Data Dictionary.  However, the Data Dictionary is also a dynamic document, and its maintenance will be the responsibility of the Data Governance Council.