Session Number: 4611
Track: Academic Advisement
Sub-Categorization: Advisement/Degree Progress Reports
Session Type: Presentation
Tags: 11g, 8.53, Academic Advisement, Alliance 2018, PS Query, Student Records Reporting
Primary Presenter: Nathan Chakerian [Sr. Business & Data Analyst - Azusa Pacific University]
Co-Presenter: Houri Hagopian [Associate Director, Undergraduate Registrar and Data Systems - Azusa Pacific University]
Time: Mar 26, 2018 (09:45 AM - 10:45 AM)
Room: Ballroom C
Session Length - Primary Choice: Mini Session
Knowledge level : Intermediate
Target Audience: All
Learning Objective 1: To understand what the various Academic Advisement Analysis Database tables are and how they relate to one another.
Learning Objective 2: To understand why querying these tables would be beneficial to your institution.
Learning Objective 3: To understand how to report based on these table by reviewing practical examples.
Prerequisites : Knowledge of Academic Advisement configuration and PS Query.
Advance preparation: No Advanced Preparation Required
Version Presenting: PS 9.0
Level of Customization: None or N/A
Level of Partner Integration: Institution Alone
Project Phase: Production
Project Go Live: Earlier than 2017
Your Training in this Area: I have been trained in-house on the AA/CC/SR modules.
Description: In an effort to make proactive and data-driven decisions, Azusa Pacific University (APU) has built queries that mine the data in the Academic Advisement Analysis Database tables. An institution can identify which students are taking a specific class to meet a particular requirement. It can count how many students still need to satisfy certain General Education requirements. It can even get an idea of how many class sections of a course might need to be offered next semester. Understanding how the AA tables relate to one another is key to embarking on this mission to report this data accurately. This session will discuss the various AA tables and why an institution would want to query them. It will even provide a handful of practical examples of the types of queries APU has been able to build.