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Why is my data different from yours?

Download this page as a document (pdf, 52KB).

All reports pull data from the same source—the SIS system.  This is where data is entered and stored.  Since all reports use the same source, why do reports showing the same things sometimes differ?  In a nutshell, because the answer is that they are being pulled in different ways.

Over the years, FHDA has developed different methods for extracting data based on new technologies and changes in systems.  As new systems are developed, older systems are temporarily supported over a transition period and then may continue to operate indefinitely—but are not being supported behind the scenes.  This means that reports may not get updated to support new rules or that servers are not maintained.

Because each system is built upon different technology, it is impossible to create reports that are 100% identical across systems.  Even if the overall logic is similar, core differences in the systems means that data is pulled, stored, and presented in slightly different ways.  This is a result of software and servers—not of people.

Another key factor is that many reports actually pull from databases that are mirror copies of the SIS system, rather than from SIS itself.  If the SIS system had to respond to all our queries in addition to the normal activity occurring in a typical day, the system would slow down because it would be trying to do too much at once.  By creating these “mirror images” for different tasks, response time is faster all around.  It would take a lot of processing power to update these “mirror images” every time the main SIS system is updated.  Instead, the “mirror images” are updated on a regular basis (from one to several times a day, depending on the database).  As a result, these mirror databases are not “real time”—but they are pretty close, with just a bit of a lag.  During busy times (such as opening week) the system may change enough that you notice differences, but typically the lag is not even noticeable.

Timing is also plays an important role.  When data is “live,” rather than “frozen,” it can change at any moment as new information is being added and corrections are being made every day—even to data from years past!  Most reports at FHDA are based on live data since it is the most accurate, but as a result you may notice slight differences in data on the same report generated at different points in time.
Finally, because reports are being designed at different points in time by different people, sometimes choices are made that result in different data appearing on what would seem at first glance to be an identical report.  For example, if you want to look at FTES for the current term, you could get very different numbers if one report uses “estimated FTES” and another uses “actual FTES” and another uses “end of term FTES.”  If we’re three weeks into a term, we may not have accrued much Positive Attendance hours—and each method of pulling FTES will calculate FTES differently:  estimated—assumes 100% of all positive attendance hours loaded for a course; actual—shows only the FTES that has currently been generated in those first three weeks; end of term—only shows the actual FTES generated across the full term, and thus is zero until a term is complete.

Here are a few common report sources and a little about them:


STUDENT DATA REPORTS

Report Type

Access

Data Source

Refresh Frequency

MAUI

FHDA staff with older Apple computers

MAUI database

Throughout day

MAUI Replacement Reports
(a.k.a. Hyperion Reports)

FHDA staff with Merced access

Francine database

Throughout day

Research Database

FHDA researchers only

Debbie database

Once nightly

Note that even though the MAUI reports and the MAUI Replacement reports are based on databases refreshed throughout the day, they may refresh at different times.

In the end, all the reports ARE based on the same data—but it can get confusing!  The best thing to do is to read any notes that are generated at the top or bottom of a report—these give you a clue as to the logic used to generate that report.

I hope this helps to explain some of the “why” behind the numbers.  Don’t hesitate to contact me with questions.

Daniel Peck
Supervisor, Research & Planning
peckdaniel@foothill.edu
650.949.6198

 

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