1. Student Admin Data Reporting from PeopleSoft SA DePaul University: Three years, three (concurrent) approaches! Jim Janossy and Russ Patterson DePaul Information Services Ed Schaefer, Enrollment Management Research

2. Jim Janossy - DePaul Information Services –Student datamart development and popularization Ed Schaefer - Enrollment Management and Marketing, Reporting and Research –Informatica ETL and BI decision and future DW Russ Patterson - DePaul Information Services –Informatica ETL and BI decision and future DW Presenters and Panel

3. Start simple and stay focused Establish a naming convention early Prototype and pilot first Keep security simple (ACAD_GROUP) Roll out useful things as you go “Market” to users, do ongoing training Get your documentation onto the web! Cutting to the chase...

4. Student datamart –PS table extracts packaged for easy use by 160 casual users –Aim: day-to-day meat-and-potatoes selection and contact data for the enrolled and active student population –Not intended for statistical reporting Enrollment Management Research databases –Current statistical reporting and census captures –Admission reporting and day-to-day college admin stats –Marketing measures and EM decisionmaking OIPR databases –Moderate to long term statistics and trends –IPEDS reporting Three level of approach

5. Cadre of willing users Increased user self-service willingness and capability Ability to integrate SA, HR, Finance Staged replacement of initial products Justification for a higher level ETL and BI Leads to...

6. Student datamart Access, SQR EMR databases Perl, SQL-Server, Access OIPR databases ODBC, SQL-Server, DTS Cognos Leads to... Decision: Acquire a standard ETL and BI Need for portal delivery Need for administration via web Need for dashboards Credits acquired with EPM

7. Reporting instance PeopleSoft Student Admin system Common base: Reporting instance is a full copy of the on-line system

8. Three level of approach Student datamart –PS table extracts packaged for easy use 160 casual users –Aim: day-to-day meat and potatoes selection and contact data for the enrolled and active student population –Not intended for statistical reporting Enrollment Management Research databases –Current statistical reporting and census captures –Admission reporting and day-to-day college admin stats –Marketing measures and EM decisionmaking OIPR databases –Moderate to long term statistics and trends –IPEDS reporting

10. Limitations Limitations spreadsheet maximum 65K rows spreadsheet maximum 65K rows hard to learn data structures! hard to learn data structures! awkward outer joins awkward outer joins PS-Query 338 users Data

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13. Low- hanging fruit!

14. What users did What users did PS-Query 338 users Data Access

15. Datamart approach Datamart approach PS-Query 338 users Data Datamart Access

16. You can combine! You can combine! PS-Query 338 users Data Datamart Access Links to spreadsheets Links to tables Local tables Data

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18. Datamart Access spreadsheet maximum 65K rows spreadsheet maximum 65K rows hard to learn data structures! hard to learn data structures! awkward outer joins awkward outer joins Why datamart? Why datamart?

19. Student datamart functional look 22 tables 22 tables Enrolled student data Enrolled student data Assemble data for convenient use Assemble data for convenient use Focus on 20% to meet 80% needs Focus on 20% to meet 80% needs Row control by ACAD_GROUP Row control by ACAD_GROUP

21. PeopleSoft operator id and password

22. Usage

23. Student datamart technical look Separate Oracle database Separate Oracle database Oracle define, create, security Oracle define, create, security Extract data with Access or SQR Extract data with Access or SQR Load with SQR or SQL*Loader Load with SQR or SQL*Loader Pilot first, engage users, perfect it Pilot first, engage users, perfect it

24. Example: Best Contact Data Table ADDRESSESNAMESPERSONAL_PHONEEMAIL_ADDRESSES HR: employees CBORD: dorm assigns Barat dorm assigns DP701A Best Contact Data

25. One datamart table!

26. Goals Clear documentation Clear documentation Clear naming convention Clear naming convention Create simple data structures Create simple data structures Interpret coded values for use Interpret coded values for use Use common tools, common skills Use common tools, common skills

27. For table building... Common tools Common skills Common cents ODBC MS-Access SQR SQL*Loader Oracle roles

28. Common tools Common skills Common cents Existing skills MS-Access Excel Basic PC training Views by college For users...

29. Common tools Common skills Common cents For DePaul... Low cost Short lead time Low overhead Meets 80% need In place now

30. For more info... See the DePaul datamart web site at www.depaul.edu/~datamart

31. Data access blossoms with DePaul’s datamart! The DePaul University Student Datamart contains data about currently enrolled students extracted from the PeopleSoft student administration system and staged for quick retrieval to meet adhoc information reporting needs. The datamart is provided for use as a regular resource to administrative personnel in the university community. This web site provides background information, instructions for gaining access to the mart, and documentation for the 23 datamart tables. Questions? OverviewAccessExamplesTrainingDocumentation If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Table of Contents

32. Overview: How the Datamart grows! DePaul Information Services began analysis and construction of the student datamart in 2001 after implementation of the PeopleSoft student administration system. The datamart is housed as a special collection of data tables in an Oracle database. Users gain access to the datamart via ODBC connection and typically use Microsoft Access as their data extraction and reporting tool. The core of datamart users is 50 administrative personnel in all nine college of the university. Follow the flowers to see how the datamart grows! Questions? IntentTable listTable loading If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page User reactionScopeExtraction

33. Access to the Datamart Access to the student datamart is provided to administrative personnel whose job responsibilities require the ability to acquire and use student information in their daily work. All datamart users must be authorized PeopleSoft system users, and in addition must file a request for mart access. Datamart users in college offices receive access to data for students enrolled in their respective colleges, while executive department users can access student data across the university. Questions? View controlRequest form If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Tom Paetsch, Data Administrator Enrollment Management DetailsAccess policy

34. Information Extraction Examples “Since gaining access to the student datamart, I have been able to do information extractions I previously had to depend on programmers to do. Using the mart has made it much faster and easier for me to get data I need!” says Cheryl Barkby of DePaul’s ID Card Services Division. “I typically need to identify the enrolled student population that meets requirements for the U-Pass program, and obtain their addresses and process interface files to the CTA. The datamart really helps me do my work!” Questions? Linking to PS-Query spreadsheets Frequently asked questions Labels If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Cheryl Barkby, Analyst ID Card Services SamplesHow to...Reports

35. Datamart Training The student datamart was designed specifically to ease the burden of data access to a complex student administration system. A major effort in the design was directed toward extracting and staging the data that experience has shown most college offices need to conduct their day-to-day work effectively. In order to help college office administrative personnel use the datamart effectively, we’re providing a number of training resources in collaboration with ongoing Human Resources office software skills training. Questions? ODBC connectionSchedule If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Happy campers in classroom training! Suggested preparation Links to training sites

36. Datamart Documentation The content of each datamart table is documented in a spreadsheet that shows the column name, format of the column, and the PeopleSoft table and column from which the data is drawn. You’ll also find access here to explanations of certain data columns as well as the SQL used to extract and form the datamart tables. Review, comments, and suggestions concerning this documentation and table formation logic is welcome. Questions? Table definitions Table formation SQL If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Gino Kao Programmer, Infrastructure Group Data explanations

37. Datamart Documentation The content of each datamart table is documented in a spreadsheet that shows the column name, format of the column, and the PeopleSoft table and column from which the data is drawn. You’ll also find access here to explanations of certain data columns as well as the SQL used to extract and form the datamart tables. Review, comments, and suggestions concerning this documentation and table formation logic is welcome. Questions? Table definitions Table formation SQL If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Gino Kao Programmer, Infrastructure Group Data explanations Data origin documentation

38. Documentation

39. Datamart Documentation The content of each datamart table is documented in a spreadsheet that shows the column name, format of the column, and the PeopleSoft table and column from which the data is drawn. You’ll also find access here to explanations of certain data columns as well as the SQL used to extract and form the datamart tables. Review, comments, and suggestions concerning this documentation and table formation logic is welcome. Questions? Table definitions Table formation SQL If the information at the selection buttons above still leaves you with questions or you need additional help, please e-mail Jim Janossy, Russ Patterson, or Gino Kao. To Home Page Gino Kao Programmer, Infrastructure Group Data explanations SQR source code download

40. What do users say about the student datamart ? “We’ve found that while we can look up students one at a time online using PeopleSoft, we can use the datamart to access data to get lists of enrolled students and related information, without having to ask for special programming in each case!” Mike Medin ID Card Services Office Tanicha Hart College of Liberal Arts and Science “We’re using the student datamart to identify incoming freshmen and prepare mailings to them. We have conducted in-house datamart training sessions and find that getting people up to speed on datamart access is easy and quick to accomplish!” DePaul University Copyright 2003 DePaul University Chicago, Illinois USA www.depaul.edu

41. Charles Moore School for New Learning Marcelo Lanzarotti Information Services Division “The datamart lets us get data for operational reporting and analysis that we just couldn’t get before! And it has given me new opportunities to learn modern data access techniques and presentation. My new skills have allowed me to grow in areas that are also essential for higher education achievement. Everyone can benefit from the Datamart's user friendly interface!” “The datamart lets us retrieve student information to meet adhoc requests from many users quickly and efficiently. We handle over 300 requests a year using the mart, and this is only a small part of what we do in this area of information services.” DePaul University Copyright 2003 DePaul University Chicago, Illinois USA www.depaul.edu

42. Jennifer Hoover College of Liberal Arts and Sciences “As a frequent user of the Student Datamart tables for nearly a year, I find it a highly reliable, integral and overall indispensable resource for generating a diverse collection of student reports. Moreover, the datamart immensely reduces turnaround time for my report requests. Reports that formerly required three or four separate queries in PeopleSoft Query can now be completed right in Access by way of the datamart tables, often from only one query! Within the College of LA&S departments now receive more detailed and accurate quarterly reports about their students. Usage of the student datamart played a large part in these reporting improvements.” DePaul University Copyright 2003 DePaul University Chicago, Illinois USA www.depaul.edu

43. “The student datamart is a great tool for our information gathering needs. The aggregated data allows for the creation of much simpler queries than can be written in PeopleSoft Query. We can create easy-to-access queries and reports that are much simpler to understand, change and run for users of different skill levels. Whether it is targeted mailings or analyzing student history, we are continually finding new uses for the datamart that allow us to better serve our student population!” Mark McMurray School of Computer Science, Telecommunication, and Information Systems “The datamart is very useful to SNL in our day-to-day operation since it provides a fast and convenient way to extract data we need for decision-making. We look forward to using the datamart even more to meet many of our needs for information about our classes and students!” Doug Murphy Senior Assistant Dean School for New Learning DePaul University Copyright 2003 DePaul University Chicago, Illinois USA www.depaul.edu

44. Three level of approach Student datamart –PS table extracts packaged for easy use 160 casual users –Aim: day-to-day meat and potatoes selection and contact data for the enrolled and active student population –Not intended for statistical reporting Enrollment Management Research databases –Current statistical reporting and census captures –Admission reporting and day-to-day college admin stats –Marketing measures and EM decisionmaking OIPR databases –Moderate to long term statistics and trends –IPEDS reporting

45. Department in Enrollment Management (EM) –Integrates traditional enrollment services (admission and financial aid, for example) with our university’s marketing and communication activities, as well as alumni and career networks –EM’s Goal: Improve and enhance DePaul’s competitive market position and prominence in Chicago, the nation, and the international community EMR’s Goal: Provide timely information that is valuable to understanding and enhancing DePaul's market position and prominence –Reporting –Research Enrollment & Marketing Research

46. Reporting –Admissions Yield Reports Prospect Reports Mailing Lists –Enrollment Weekly Enrollment Comparisons Daily Enrollment Reports Research –Prospect Analysis (prospects to enrolled) –Market Analysis (program success) Enrollment Data Capture began in 1990 Admission Data Capture began in 2000 Some Research/Reports required data from both captures –Trick was getting the two to tie-out –And getting the data to the requestor quickly EMR Information Needs

47. PeopleSoft Daily Enrollment Daily Admissions ETL Oracle PERL, T-SQL, Stored Procs Adm Reports Specialized Adm DBs Enr Reports TEAMS Elite Housing DB Current Future SQL Server EMR Data Warehouse T-SQL & Stored Procs Specialized Research DBs Specialized Reports Research & Report Oriented ETL SQL Server Enrollment & Marketing Research Enrollment Management DePaul University Data Stores

48. Three level of approach Student datamart –PS table extracts packaged for easy use 160 casual users –Aim: day-to-day meat and potatoes selection and contact data for the enrolled and active student population –Not intended for statistical reporting Enrollment Management Research databases –Current statistical reporting and census captures –Admission reporting and day-to-day college admin stats –Marketing measures and EM decisionmaking OIPR databases –Moderate to long term statistics and trends –IPEDS reporting

49. Census Files created from Oracle via ODBC and SQL-Server DTS Integrated Finance, Student, Instruction, and Faculty data serves as official stats Student data set is consistent with historical categories at aggregate level Student census files coordinated with EMR Reports developed in varying degrees of sophistication (reports to OLAP cubes) Office of Institutional Planning and Research (OIPR)

50. Cognos is used against SQL-Server Reports have 3 levels: –OLAP driven static web reports with no interactivity (put up reports quickly) –OLAP driven web reports with drop downs. (customized web reports with interactivity) –OLAP interactive browser: fully analyze data from basic browsing to data mining Office of Institutional Planning and Research (OIPR)

51. Warehouse PowerCenter Meta Data Repository PowerAnalyzer Meta Data Repository Multiple schemas HR Finance SA Non-PS PowerCenter Client Tools PowerAnalyzer Reporting Web Server PowerCenter ETL EPM BI ETL Informatica Data Warehouse PowerCenter/PowerAnalyzer + PS EPM Portal delivery!

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