Data Definition/Data Mart Project Phases

The development of data marts in MyUNLV Analytics involves a team comprised of data stewards, data users and IAP development staff. The team's collaborative process centers on the creation and implementation of institutional data definitions, as outlined below.

Data%20Mart%20Development%20Schematic

1. List Informational Needs and Elements.

Through regular meetings, data stewards and users work with IAP to communicate and list informational needs around a specific purpose, or for a given subject area.  The team creates a list of conceptual informational elements designed to address these needs.

The work performed in this step defines what will be used in a data mart and for what purpose.


2. Draft Data Definitions.

Through regular meetings, collaborators work to draft data definitions for each of the listed informational elements.  A data definition describes the title, description, context, and usage of a reporting element, as well as specific instructions on how to extract or derive the reporting element from transactional data sources. IAP maintains a central metadata repository of institutional data definitions.

The work performed in this step defines how to correctly interpret transactional data to achieve the informational needs.

3. Review and Refine Data Definitions.

As data definitions are drafted, collaborators review them for accuracy and clarity, continuously refining them until they are understandable and acceptable to the team, at which point IAP creates a formal version in the central repository.

The work performed in this step ensures that data definitions are institutional in scope, well-understood, and accurate.

4. Implement Data Definitions in the UNLV Data Warehouse.

As definitions are considered complete, IAP creates and manages the processes that implement them in the UNLV Data Warehouse. This includes developing technical jobs to extract and interpret data from transactional sources, and construct tangible reporting elements that match the conceptual ones.

The work performed in this step centralizes a technical implementation of the institutional data definitions, simplifying reporting and analysis throughout the institution.

5. Construct the Data Mart.

IAP structures the newly created reporting elements into a data mart and makes them available for display through MyUNLV Analytics.

The work performed in this step allows the reporting elements to be readily used in the institution’s decision-support platform.

6. Review and Refine the Data Mart.

Data stewards and users create reports in MyUNLV Analytics using the new data mart, testing the data definition implementations, and communicating progress and issues with IAP development staff. IAP refines the data mart accordingly.

The work performed in this step exercises the data definition implementations and tests the success of the data mart for its intended purpose.

7. Open the Data Mart for Institutional Use.

IAP incorporates the completed data mart in the production reporting environment and makes it available to campus users with approved access and who have completed necessary training.