Data have the potential to inform us about what we are doing, how well we are doing it, the impact we are making, and opportunities for system improvement. Analyses of these data can produce insights that can help guide practice toward an organization’s goals and objectives. Often, evaluators collect data for the specific purpose of evaluating program processes and outcomes. Other times, though, existing data can be just as effective for evaluation purposes. Many organizations have substantial existing data that can be used to develop performance measures, understand processes, mine for unseen relationships, and evaluate inputs and outputs.

These data are often stored in organizational management information systems (MIS) and do not always present themselves for easy analysis.  In particular, data from an organization’s MIS are typically organized as relationaldatabases.

Relational databases use relationships among individual database elements to organize data at a higher level than a simple table of records. Records from a relational database must be linked and queried and rolled-up, often using Structured Query Language (SQL) to create a “flat file” for statistical analysis. Once a flat file is created, case-based statistical testing can be performed.

Human services agencies like child protection and public health, justice agencies like juvenile probation and adult probation and parole, and education systems all typically hold substantial amounts and varieties of data in their MIS’s. We work with these types of organizations on a regular basis to extract data from their systems, develop queries, link data elements and records, and roll-up records to the appropriate unit of analysis to create flat files so that existing data can be used to describe processes, evaluate practices and programs, and understand what drives outcomes.

There is substantial value in the data held in MIS systems, but it takes some skills to manipulate data in relational databases to create a file ready for analysis and evaluation. This session will offer a primer on this manipulation. It will cover the general structure of relational databases, the basics of how to use SQL to access those data, an introduction to writing queries, linking data elements, and rolling up data, and the processes of using existing data to inform practice.

The purpose of this demonstration will be to introduce evaluators to the tools and concepts for using data in an organization’s existing relational databases for developing data-driven insights into programs, practices, and impacts.