Title: Increasing information efficiency at lower-cost: single versus multiple product approach to information retrieval

Transcription

1 Office of Planning and Analysis (OPA) Page 1 of 48 (10/20/2011) Presenter: David Wright, Wichita State University Event: 2011 Educause Conference, Philadelphia PA, October 20 th, 9:00-9:50am Title: Increasing information efficiency at lower-cost: single versus multiple product approach to information retrieval Abstract: IBM SPSS Statistics is used as an ETL engine to build and refresh an integrated student/course data system from which analyst use a Source-Code-Object process via SPSS Statistics to deliver information for evidence-based decision-making related to internal policies, auditing, review and assessment thereby increasing information efficiency at reduced cost. Bio: David Wright is Assistant Vice-President for Strategic Planning and Business Intelligence at Wichita State University. In addition to these duties he also serves as chief architect of the Business Intelligence and Predictive Modeling (BIPM) system, Professor of Sociology and provides training in data management and statistical analysis. Copyright, David Wright, Wichita State University, This work is the intellectual property of the author. Permission is granted for this material to be shared for non-commercial, educational purposes, provided that this copyright statement appears on the reproduced materials and notice is given that the copying is by permission of the author. To disseminate otherwise or to republish requires written permission from the author.

2 Office of Planning and Analysis (OPA) Page 2 of 48 (10/20/2011) (WSU) Wichita State University is an urban campus residing in the largest city within the state of Kansas, Wichita. We are a Doctoral Research Intensive institution providing over 210 degree programs ranging from bachelors to doctoral levels with nationally recognized programs in health care and engineering (our aerospace program is #2 in the nation for NSF funding). Enrollment is approximately 15,000 students per term. (Banner) In terms of our transactional data systems, we are a Banner school running their student, finance, financial aid, HR alumni modules across a mixed server environment of Oracle and Microsoft SQL Server on Linux, Unix & Windows. Microsoft Reporting Services is our primary web-based reporting tool. (IBM SPSS Statistics) In terms of IBM SPSS products, we have a 500 seat license for IBM SPSS Statistics Client (base, regression, advanced) used primarily for instruction & research; IBM SPSS Statistics Server and Collaboration & Deployment Services is used exclusively for our Business Analysts; many of our business analysts also employ Single User modules to extend SPSS functions (e.g., forecasting, custom tables, neural networks, etc.). There are other SPSS products on campus such as SPSS Data Collection and AMOS but they not related to enterprise use. (SPSS Users) In terms of SPSS users, we have 3 groups comprising instructional (classes in methods and statistics), research (faculty & graduate students) and business analyst within units across campus. Business analysts are the focus of today s presentation.

3 Office of Planning and Analysis (OPA) Page 3 of 48 (10/20/2011) We have business analysts across campus who must respond to information requests daily from administrators to inform decision-making within their units. The type of information they are asked to deliver does not lend itself to normal reporting, these are usually specialized queries often taking place within meetings. These information requests must be responded to quickly in order for true evidence-based decision-making to occur which means that business analysts must be able to access information near instantaneously. Data-based information delivered after the meeting or the next day is often too late to be useful. In other cases, they are asked to produce an indepth analysis but in a short time period. In either case, information retrieval must be a quick and speedy process. We are a mid-size institution, so cost can be a limiting factor in providing support, especially in areas not directly tied to day-to-day operations. Yet we have the same needs for timely information that large enterprises with large budgets have so it s imperative that we find information solutions that can fit our needs for information and our budget. So our goal is to increase the efficiency of which analysts within units can retrieve information for decisionmaking, mindful that efficiency must be defined in terms of speed and cost.

4 Office of Planning and Analysis (OPA) Page 4 of 48 (10/20/2011) We have several obstacles to information efficiency that we must overcome to reach our goal: (Banner data system) Our Banner data system is a transactional-based relational database comprised of thousands of normalized tables; while this configuration makes day-to-day operation processing efficient, it is a highly inefficient method for informational retrieval. Business analysts, even for some of the more simple information request, must join several tables all of which takes time and requires extensive table knowledge. (Reporting Services) Microsoft Reporting Services provides us with a low cost method to deliver web-based reporting but it is, at best, a general reporting tool and one that is not suited to single-use queries. Most of our business analysts do not have the skill to create reporting views meaning they are reliant on IT staff increasing the lead time for development. In addition, Microsoft Reporting Service views are dimensionally limited and static based on the report s defined parameters meaning deeper drill downs into the data are not possible or too lengthy in report execution time; and as most business analysts will attest, when they provide information to others it more often elicits more questions than answers requiring them to dig deeper within the data system and beyond what reporting services can deliver (IT programmers) While we are blessed with a high skilled and creative IT staff (on both the system and programmer side), like most IT units, they are under staffed and their top priority is maintaining Banner s transactional processing and general reporting that meet the needs of the largest set of users, so they have little time to respond quickly to the needs of individual business analysts. More importantly, even if they were fully staffed, IT programmers lack knowledge of the business practices that take place within units so they are often not suited to making judgments about what data are best for the question at hand, that can only be answered by those who use the data daily and who are aware of the constant changes in business practices, rules and regulations. (Analysts) Among our business analysts, some are highly skilled, but most have little to no sql experience making them reliant on reporting services which can only address general queries, or IT programmers who do not have the time or unit knowledge to respond in a timely fashion, meaning most are obtaining their information from data warehouses (a 1990s form of information technology); all of which means that information retrieval is a lengthy manual process that is very inefficient.

5 Office of Planning and Analysis (OPA) Page 5 of 48 (10/20/2011) Our solution to these problems was to create a unified data/information system, one that addressed 5 elements: 1. Data Table Consolidation: Extracting data from a relational database comprised of thousands of normalized tables is not an efficient means to obtain information; instead, business analysts need a small set of denormalized tables that provide an integrated data system from which they can obtain 95% of all information queries, One Stop Shopping. 2. Centralized Access: Getting to data should be easy and secure, as easy as opening Windows Explorer & navigating to a folder & double clicking a data file, a common PC interface that is ubiquitous. It should also be a place where analyst can share information and store documents related to the data they & others use. 3. Transparency: Business analyst must have complete documentation for the data from which they obtain information including source code, data dictionaries, data maps, directory listings and other documents that provide guidance and context to the data they use. Such information breeds confidence in the data business analysts use and is needed for analysts to explain where the data came from to others. 4. Open Source Input: Business analyst have extensive knowledge of unit specific business practices, knowledge which should be shared among data users and to inform data development. 5. Single Product Platform: Both the back office operations connected to data consolidation and the front office operations of analyst extracting & delivering information should be based on a single product for reduced cost and increased speed of delivery. Using multiple products for information is inefficient IBM SPSS provides the product platform that unifies the entire system from data generation to information delivery. At Wichita State University we refer to this system as the Information System.

6 Office of Planning and Analysis (OPA) Page 6 of 48 (10/20/2011) We need to move from the relational model of disparate normalized tables to a small set of denormalized tables to increase information efficiency. An integrated student/course system that allows analysts to obtain data on students and courses throughout the entire migration process through the university (horizontal) including the ability to integrate across divisional units (vertical) to provide additional context, one stop shopping for 95% of all data queries for student & course information.

7 Office of Planning and Analysis (OPA) Page 7 of 48 (10/20/2011) A unified data system that provides a single source for all 3 phases of student migration from incoming (prospects, applicants, etc.) to in-process (registration, classes, etc.) to out-going (degrees). When I open registration activity I should have access to current & the complete history of in-process activity; likewise, within that table I should also have access to the complete in-coming (application) activities, horizontal integration across the entire student migration process. In addition, I should be able to see all cross-divisional unit related data so when I m looking at registered students I should also see their financial aid, out of pocket expenses, if they are in housing, their alumni network, etc., a vertical integration of data across divisional units.

8 Office of Planning and Analysis (OPA) Page 8 of 48 (10/20/2011) We achieve this integration via 3 processes:

9 Office of Planning and Analysis (OPA) Page 9 of 48 (10/20/2011) Back office operational processing that creates the integrated denormalized tables;

10 Office of Planning and Analysis (OPA) Page 10 of 48 (10/20/2011) Front office task processing that converts the denormalized data into information and provides information object delivery

11 Office of Planning and Analysis (OPA) Page 11 of 48 (10/20/2011) And a feedback loop that takes advantage of the knowledge among business analysts and their business practices for continued source development.

12 Office of Planning and Analysis (OPA) Page 12 of 48 (10/20/2011) Returning to our need for table consolidation, during back office operations, from our Banner production relational databases, IBM SPSS Statistic Server is used to execute SPSS syntax files nightly for automated ETL builds for the BIPM student/course data. The BIPM primary data architect can also run SPSS syntax files manually from IBM SPSS Statistics Client to test and build new BIPM features.

13 Office of Planning and Analysis (OPA) Page 13 of 48 (10/20/2011) In this slide we view a small segment of code from the SPSS syntax files that the SPSS Server executes nightly. SPSS provides the ability to use multiple programming languages including sql, pyhton, R, host commands in addition to standard SPSS command syntax. In fact, SPSS supports the use of different sql languages (oracle vs MS sql) WITHIN the same code file and can import/export data from different server platforms (e.g., oracle, microsoft, etc.) all WITHIN the same code file, its platform invariant. In addition to supporting multiple programming & platforms, we quickly discovered a considerable speed advantage in NOT using full sql builds (or sql pushback) even in cases where we are processing tens of millions of records. Importing slightly sql managed tables (e.g., limited joins, distincts, etc) into SPSS and then performing the table joins and other common sql tasks within SPSS increased our ETL speed on average to a 1 to 5 ratio, for every 5 minutes of sql server processing (sql pushback), SPSS could perform the same builds in 1 minute.

14 Office of Planning and Analysis (OPA) Page 14 of 48 (10/20/2011) We also automate via SPSS syntax modeling to score students and institutions (e.g. high schools, universities etc.). In this slide we are executing several logistic regression models for different populations related to their probability to be on academic probation by the end of their first year, a score that is available to both SPSS and non-spss users to identify students at academic risk. In addition to storing these scores in the BIPM SPSS *.sav files for business analyst use, these scores are uploaded via SPSS Server into our Banner production system tables nightly to allow non-spss university personnel access to student or institutional scores for decision making.

15 Office of Planning and Analysis (OPA) Page 15 of 48 (10/20/2011) The automated modeling has allowed us to significantly increase ROI for recruitment and retention and do so at lower cost. We used to pay outside vendors thousands of dollars yearly to score our prospects, something we do now internally with SPSS. We know our data better than outsiders & can tweak our models to meet our conditions and as seen in this slide produce stronger predictive models than our outside vendors. We now use SPSS scoring to perform targeted recruitment based on student & institutions who display the greatest likelihood of coming; since the introduction of scoring, we ve seen over a 13% increase in recruit-to-applicant yields from mailings and site visits. We also have models that score for academic at-risk, retention, degree completion, all of which provide business analysts and non-spss users (we upload these scores to our production system) with data for decision-making.

16 Office of Planning and Analysis (OPA) Page 16 of 48 (10/20/2011) In addition to the nightly ETL builds of the BIPM SPSS *.sav files for analyst use, we also use SPSS Server to produce non-spss dbo objects during front office processing tasks, these are used to allow non-spss products (e.g., Microsoft Reporting Services) access to SPSS-defined information to provide for the entire university user set.

17 Office of Planning and Analysis (OPA) Page 17 of 48 (10/20/2011) In this Microsoft Reporting Service view we use SPSS data to identify students who are at academic risk and their course pre-registration activity. Advisors can use the report to take steps to have the student switch enrollment to another course before classes begin to avoid further academic jeopardy. The INC score is a model defined scoring that occurs in the nightly ETL builds that is also uploaded into our Banner student system for access to non-spss users. Student who score below 25 are at academic risk to fail within their first year. Even though this student has a 22 ACT & an entering HS gpa of 3.11, their INC score of 25 tells us this student is at-risk. This is born out by the current standing of 1.58 gpa for the last 25 hours earned in their first year. In addition, SPSS has identified classes which place this student at higher risk (classes which have higher than normal D/F grade distributions), classes for which the student does not have preparation to succeed. This is the essence of predictive analytics, identify risk before harm occurs. The advisor can take action to have the student change their courses before class begin to avoid more harm and to steer the student to courses that will prepare him/her for greater academic success.

18 Office of Planning and Analysis (OPA) Page 18 of 48 (10/20/2011) Business analysts need secure but easy access to data, access that should be centralized to one entry point and one that allows them to activate both data & program simultaneously. In addition, this centralized information portal should allow for the storage and sharing of documents among the business analyst community.

19 Office of Planning and Analysis (OPA) Page 19 of 48 (10/20/2011) We provide that centralized access point & delivery from a secured network share which our IT system engineers manage via file & folder security. This provides a single location for all business analysts, giving access to SPSS data, data documentation and documents that are shared among users. Using the ubiquitous Windows Explorer makes it easy for analyst to navigate, simply double clicking on *.sav data file to open SPSS Client to use the data generated from the SPSS Server. This also provides a central source for analyst to find the BIPM SPSS data files (SPSS *.sav files), source code (SPSS syntax files), documentation and BIPM/SPSS Community documents. This centralized network share is also set to the same logical drive letter so that users across the campus can share the same SPSS syntax files helping to foster collaboration and sharing and minimizing unit silos. For example in this slide the highlighted file BIPMS_adm_applications.sav is a denormalized table that includes 54 separate Banner tables joined as one that provides admissions a single table to get complete admission information, one stop shopping. Below that is the source code (BIPMS_adm_applications.sps) for this table and below that is the data dictionary (BIPMS_adm_applications.xlsx).

20 Office of Planning and Analysis (OPA) Page 20 of 48 (10/20/2011) Analysts must have confidence in the data they use for information, and knowing how and what data are used for their source data is crucial to gaining that confidence and providing them the means to explain to others the data they use for information. Accordingly, via the centralized portal, we provide several forms of documentation from source code, data dictionaries, to data mappings.

21 Office of Planning and Analysis (OPA) Page 21 of 48 (10/20/2011) In this slide we see the beginning of the SPSS syntax source code file for the BIPMS_adm_applications.sav file, users can quickly search through the file to see how columns were extracted and transformed. This file contains joins from 54 production based tables, comprising 79 pages of mixed sql and SPSS command syntax giving business analysts completed documentation to which base tables and columns were used.

22 Office of Planning and Analysis (OPA) Page 22 of 48 (10/20/2011) Here we see a data dictionary, available for all BIPM tables and located in the same centralized access point. The data dictionary provides the analyst with information on where columns are derived, formats, and user notes.

23 Office of Planning and Analysis (OPA) Page 23 of 48 (10/20/2011) In addition to the information related to column source, we also provide within the data dictionary a 500 count random sample of what they will find in the SPSS generated denormalized table.

24 Office of Planning and Analysis (OPA) Page 24 of 48 (10/20/2011) In addition to source code (SPSS syntax file) and data dictionaries, we also provide mappings related to base tables so they can visually see dependencies.

25 Office of Planning and Analysis (OPA) Page 25 of 48 (10/20/2011) They can also see dependencies related to SPSS and production tables, as well as time sequencing of table builds.

26 Office of Planning and Analysis (OPA) Page 26 of 48 (10/20/2011) As noted earlier, business analyst have the most up-to-date knowledge of business practices within their respective units, knowledge which is crucial to knowing which data are best and how to interpret that data.

27 Office of Planning and Analysis (OPA) Page 27 of 48 (10/20/2011) The BIPM system calls upon the expertise of business analysts when creating or modifying the nightly automated ETL builds for the BIPM data in order to best meet the needs of the BIPM/SPSS community of business analyst users. These communities also provide discussion across units reducing system silos and providing analysts better understanding when using cross-unit data. On any given day, within the communications among our analysts, you witness the sharing of this knowledge which has traditionally not been common. Now an analyst can pose a data query question to the community and obtain answers to what data should be used and even have others provide SPSS syntax scripts to help in the data retrieval.

28 Office of Planning and Analysis (OPA) Page 28 of 48 (10/20/2011) Finally, analyst are made more efficient by performing the complete data-to-information-to-object process in one product. Having to use many products to generate an information object is inefficient and costly in both budget terms and work effort.

29 Office of Planning and Analysis (OPA) Page 29 of 48 (10/20/2011) Using IBM SPSS Statistics Client, our business analysts pull data from the SPSS generated denormalized tables, perform the data management necessary to transform the data to information, and then create the information object for delivery to administrators and others for decision-making. By doing so in one product, they save time, reduce training cost and contain budget cost related to licensing.

30 Office of Planning and Analysis (OPA) Page 30 of 48 (10/20/2011) SPSS provides both a menu-based interface and programming code interface. Our analysts are instructed to use SPSS command syntax (the programming interface) when accessing the BIPM data system to take advantage of all the data management commands available in SPSS, the ability to use other programming languages (like sql), the ability to join BIPM data to live Banner production data, to have stored history (syntax comments), to run files repeatedly and to share with other BIPM/SPSS users. Here we have a syntax file in which a business analyst is pulling live Banner production data using embedded sql and joining it with a SPSS BIPM data file. From this process they can deliver any number of information objects (see next slides).

31 Office of Planning and Analysis (OPA) Page 31 of 48 (10/20/2011) Here we examine daily registration activity comparing it to last year to see which student classes are up or down during registration activity.

32 Office of Planning and Analysis (OPA) Page 32 of 48 (10/20/2011) Since we now have access to 30 years of data (from a single SPSS generated denormalized table), we can use SPSS to compare how currently registered students compare to the past, here we examine the percent of students enrolled fulltime and can see we ve made considerable progress in increasing full time enrollment which enhances retention and revenue.

33 Office of Planning and Analysis (OPA) Page 33 of 48 (10/20/2011) They can also predict future outcomes as is done here using SPSS forecasting of fall registration credit hours, important information for our budget offices as they make adjustments based on enrollment trends.

34 Office of Planning and Analysis (OPA) Page 34 of 48 (10/20/2011) Other analysts may have an interest in identifing which institutions produce the highest yield of applicants for recruiting, as is done here in examining transfer students from community colleges.

35 Office of Planning and Analysis (OPA) Page 35 of 48 (10/20/2011) As well as see where gains & losses have occurred over time in terms of an RFM analysis ranking of community college feeders to where gains and losses have occurred related to an institutions ability to provide return on recruitment effort.

36 Office of Planning and Analysis (OPA) Page 36 of 48 (10/20/2011) They can examine events such as class grade distributions and using decision trees to help classify the different groups and factors that are significant; here we see that freshmen who have lower gpa levels make up the largest percentage of those who have D & F grades in courses highlighting the need to have greater advising and academic preparation.

37 Office of Planning and Analysis (OPA) Page 37 of 48 (10/20/2011) The can perform traditional RFM analysis to identify which classes have the highest ROI as is done here examining the top & bottom ten general education courses so priority is given first to our highest ROI courses in scheduling of classes.

38 Office of Planning and Analysis (OPA) Page 38 of 48 (10/20/2011) And they can use the denormalized tables to examine the scheduling of classes as is done here in mapping the number of rooms utilized for classes (excluding labs & conference rooms) in which room use accelerates rapidly till the 9:30 to 10:30 time periods, but even at that level, we are only using 78% of available space leaving room for expansion and reallocation of use. The same is true when examining student counts by time of day (heat map) in which of the available 10,000 + seats available, we are only using a maximum of under 6,000 seats. These slides are only the tip of the iceberg in terms of what SPSS can deliver, but this presentation is not about what SPSS can do in terms of analysis and output, but more to do with what SPSS can do to help deliver information efficiently and do so at low cost.

39 Office of Planning and Analysis (OPA) Page 39 of 48 (10/20/2011) Our 5 element solution provides use the ability to have data consolidation for rapid data extraction, centralized access for ease of use, transparency so business analysts have complete knowledge of the data they are using, open source feedback to take advantage of business analysts knowledge and a single product to transform data to information & to deliverable information objects.

40 Office of Planning and Analysis (OPA) Page 40 of 48 (10/20/2011) Business analyst transform data into information which is delivered as objects whether that is a report, case study, graphs, list, or even data extracts. However, old habits are hard to break. Even though we had created a unified single product platform that converted data to information via our BIPM/SPSS system, some analysts were still inclined to use it as a data warehouse, a process rooted in 1990s technology. They were pulling data (source) from BIPM, downloading it to their PC (offline source) normally as a csv or excel file, performing laborious manual data management processes (cut/paste, insertion of formulas, etc.) and then creating their information object for delivery. This process renders data obsolete since once the changes are made to the source data offline it is not possible to refresh without extensive manual work. It is not replicative and is very time consuming. Instead, we pushed hard to train our analysts to see code as the driving force to information object generation. In this process, we use code (SPSS syntax) to pull the BIPM data (source), the SPSS syntax (code) commands are used to perform all data management tasks and to generation the output (object) of information to be delivered. This process means we are always using current data, one that is replicative and creates information quickly. No more downloading data and manual processing. The Source-Code-Object process is a more efficient means to obtain & deliver information and SPSS provides the means by which the entire process can be executed by a single product, saving time and money in the process. If all we had done was use SPSS to create a data mart or data warehouse, then we would not have advanced information efficiency. Instead, by using SPSS as a unifying means to move from data source to information object, we increase information efficiency at reduced cost. Let s look at a real-life example. A few weeks ago an analyst received an information request from a department that wanted to know for its students whether they had enrolled in their required courses, what grades they had received, a calculated gpa of the required courses and a selected set of demographics all of

41 Office of Planning and Analysis (OPA) Page 41 of 48 (10/20/2011) which they wanted as an excel file in which it was structured as one row per student. The analyst proceeded to use the old SOURCE-SOURCE-CODE process in which she downloaded the data from BIPM to her hard drive and spent hours manually configuring the excel file, not easy since the course & grade data are repeating student tables & the demographic tables are non-repeating. Then, about 3 hours into the process she received a call from the department requesting a few more variables. ALL of her 3 hours of manual work was wasted; she had to start over; so she gave us a call to seek advice.

42 Office of Planning and Analysis (OPA) Page 42 of 48 (10/20/2011) So we worked up a SPSS syntax file that pulled the data she needed and within that code performed the slotting of the course & grade data, created the calculated gpa values the department requested, joined the selected demographics and exported the results into an excel file as the department requested, the code took just a few minutes to create and if the department changed their minds we could easily go back into the code & make changes as well as repeating it for future terms.

43 Office of Planning and Analysis (OPA) Page 43 of 48 (10/20/2011) We sent her the syntax file & had her execute the code in SPSS. The entire job (which pulled from several source tables that had millions of records) extracted the data (source), performed the data management (code) & created the excel file (object) in under 7 seconds! This exemplifies the unified BIPM/SPSS source-code-object process; business analyst can get up-to-date information & have deliverables nearly instantaneously using a single product platform without downloading data and wasting time in laborious manual tasks.

44 Office of Planning and Analysis (OPA) Page 44 of 48 (10/20/2011) Review list of benefits (see slide)

45 Office of Planning and Analysis (OPA) Page 45 of 48 (10/20/2011) Despite the benefits we ve derived from IBM SPSS, there are still issues that limit its use, nearly all these center around non-spss users on campus. To push our BIPM data out to a wider audience, we need other campus supported IT products to be able to open/read the SPSS *.sav files (we are in the midst of testing an IBM provided driver for this purpose). Our current work around is to create both an SPSS *.sav for our SPSS users and a dbo table in either MS SQl server or Oracle during the nightly ETL builds so that our non-spss products can access the data. This redundancy is inefficient and is a stumbling block in getting wider use of SPSS. We also need to move away from our ODBC based drivers to access production tables to OLE, an OLE that can be fully functional with unlimited joins ability similar to our ODBC drivers. We need to deliver web based reports, allow users to mine data via cube dimensions and create dynamic dashboards; while SPSS is not designed for such things we can use the SPSS ETL builds from the BIPM system to provide source data for such processes. This is where products like Cognos come into play, but again, as a mid-size enterprise, cost can be a limiting factor.

46 Office of Planning and Analysis (OPA) Page 46 of 48 (10/20/2011) Returning to the goal.

47 Office of Planning and Analysis (OPA) Page 47 of 48 (10/20/2011) IBM SPSS provides the means for unification of the entire process from data generation to information object low cost method, substantial flexibility, leveraging business analyst knowledge and providing high quality output.

48 Office of Planning and Analysis (OPA) Page 48 of 48 (10/20/2011) Questions/Comments