Are you a QART? It’s an acronym, and it expands to Query and Reporting Tool. Most every medium to large organization has at least one. The QART is the person everyone turns to, in order to extract meaningful information from institutional data. The name, QART, is decidedly tongue-in-cheek. Even so, the job function exists because the need is real.
This need for a QART comes about for at least two main reasons. First, because although we have ever more powerful tools for acquiring data, we often lack the ability to make use of the data we acquire. Specifically, most organizations have some collection of forms and spreadsheets, all capturing and storing business critical data. Often, organizations also use packaged database applications, thereby increasing both the quantity of data. Finally, some enterprises also have automated data collection from distributed sensors. These telemetry data have to land somewhere, and so the quantity of data takes another geometric leap. Collectively, these data acquisition mechanisms result in an constantly increasing amount of data, stored in an ever increasing number of ways.
Clearly, the quantity of data poses its own challenges. Equally important, the means of storing the data also present unique challenges. For example, organizations often have data entered into spreadsheets with incompletely documented fields. Organizational databases often consist of cryptically named tables. In many instances, the application vendor regards the data schema for a particular application as proprietary information. The end result: people often lack requisite knowledge of the specifics of the way the data are stored and organized, i.e. the data model.
Enter the QART. The QART serves as an on-site expert, usually with extensive knowledge of the data storage methodologies and data models in use. Often, the QART has some familiarity with database design, and also has access to sophisticated data access tools. And the QART usually has considerable fluency with the necessary front-office applications, e.g. word processors and presentation software, to present the results of data mining efforts. Stated another way, the QART serves as an intermediary between data storage and data consumers–a kind of data broker.
The QART may be a gifted data broker, with extensive technical skills and with good customer service skills. But, especially in smaller organizations, the QART often has other, competing responsibilities. Processes for requesting and delivering reports tend to be rather ad hoc. And, because of competing responsibilities, the turnaround time for reports can be quite variable. Stated succinctly, having an individual serving as a QART “does not scale”.
So, what is an organization to do, then? Institutionalize the QART!
Start by establishing clear goals for the capability of whichever individual or group fulfills the QART responsibilities. Next, spend the time to formalize and document the processes employed by the QART. Set standards for this documentation and keep them up to date. Make sure the data models are clearly documented. Where possible, insist on data model information from the suppliers of database applications. Obtain licensed, supported data access and presentation tools. Finally, train the personnel. Make sure this training includes all the requisite tools, as well as the institutional standards for process documentation.