In the age of Big Data and Analytics, we find ourselves surrounded by data. While most of the data might reside in our Enterprise Resource Planning (ERP) system, it’s likely that there are several other ancillary data sources available to us. These sources may be...
Introduction As data is collected daily through the heavy use of computers and the internet, we continue to be plagued by the problem of dirty data. Data that is error prone or inconsistent leads to bad outcomes, such as misguided decision making (e.g. inaccurate...
More and more applications (software) are residing in the cloud. In the past, these applications were often viewed as black boxes. This means the end user sees an interface but has little insight into the processing that goes on within them. But that approach has been...
So far, we’ve taken a look at the top mistakes made during IPEDS submission and some steps you can take to reduce bad data entry during that process. But once that process is done, that’s it. Right? You’ve crossed the finish line. You’ve slain the beast! The job is...
Question: How many times have you, when reviewing IPEDS data, found basic data entry errors? Better question: How many times have you missed such errors prior to submission? The issues around data entry errors in IPEDS surveys are very real and addressing them isn’t...
The IPEDS submission process is typically not a smooth one. From accessing to collecting to validating to formatting IPEDS data, there are numerous stages where mistakes can – and often do – occur. We’ve assembled a list of some of the most common mistakes made during...
