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Sprint date

Application/Person v1 (Beth)

Engagement v1 (Helen)

Application v2 (Beth)

General

by Thanksgiving

  • Cross-check queries set up in each instance

  • Query data sent out for validation against previous external reporting (Brian Cody, Sara Abbott, IR)

  • Basic Person and Application Feeds set up in 4 instances/5 schools (Vet, Fletcher, TUSMGP, GSBS/NUTR)

NUTR

  • Meet with UCM to clarify data structure

  • start technical conversation series with Matt

by Christmas

  • connect Denodo feeds to Tableau for our testing

January 2-18, 2025

January 21- February 7

February 10 - March 1

March 4 - March 21

Phases:

A. Person

  1. Basic bio/demo data

  2. Review and revision period

  3. Advanced bio/demo data

    1. Undergraduate school

  4. Custom requests

Instance

est. delivery to DS&E

Available to Selected End Users

Review Period

Vet

Grad Hlth Sci (NUTR/GSBS)

TUSMGP

Fletcher

B. Application

  1. Basic application data

  2. Review and revision period

  3. Advanced application data

  4. Custom requests

C. Interaction/Activity/Source Data (Inquiry Details)

  1. Basic interaction activity (incl. program of interest)

  2. Review and revision

  3. Advanced interaction activity

    1. Messages

  4. Custom interaction activity

D. Messages (Deliver Campaigns)

Phase

School/Instance

Delivery Date (Slate Team)

A1/B1

Vet

C1

Vet

D1

Vet

A1/B1

TUSMGP

B1

TUSMGP

C1

TUSMGP

D1

TUSMGP

A1/B1

NUTR

C1

NUTR

D1

NUTR

What does “done” look like?

  • Query in Slate is built and configured with web services
  • Denodo “view” is built?
  • Data refresh is scheduled/ongoing
  • Field definitions are added
  • Query description is added
  • Access/permissioning is configured?

Notes:

  • Do we need a “beta” period?

  • Feedback from stakeholders/clients--how to factor that into the project plan?

  • How do we handle ongoing requests/concerns

  • Capturing the next “core fields” for the University

  • Goal is to build a dashboard that is used for all schools

  • Gather admisisons directions to create standard definitions (e.g. Veterans)

    • Under Data Governance Committee

    • Advisory vs. Directive?

  • Slate team builds the queries sent to Denodo that creates the “base view” – only for DSE

Questions for Group meeting/Matt

  • What happens to old data?

  • More access to update fields?

  • Who is in charge of naming fields/naming conventions?

  • Where do we solve the “fuzzy” definitions, in Slate or Denodo? To the “university” standard?

    • e.g. socioeconomic indicator

    • school-specific clarifications happen in Slate, University wide “joins”/translations happen in Denodo?

      • e.g., definition of “admitted” is school-specific?

      • e.g., IPEDS classification is University/Denodo?

Data Collections

  1. Person

    1. Simple bio/demo data

  2. Application

    1. Simple program/app data

  3. Engagements

    1. Lead Form submissions

    2. UCM/Hubspot

    3. Origin Sources

Instances

  1. Vet

  2. Nutrition

  3. GSBS

  4. TUSMGP

  5. Fletcher

Milestones

  1. Identify data to be provided

  2. Identify level of data inaccuracy

  3. Identify causes of data inaccuracy

  4. Retroactively “fix” inacurate data

  5. Business process to ensure data remains accurate

  6. Audit process to identify future inacuracy

  7. Slate Query v1

  8. Data review/validation

    1. Review internally (Helen or Beth cross-check)

    2. External stakeholders (Brian,

  9. Slate Query v2

  10. Refresh/Add query to Denodo

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