October 2005 — Features

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Scrubbing Data for D3M

by Neil Mercurius

Is your school or district planning to develop or purchase tools and technologies to better enable data-driven decision-making (D3M)? First, you’ll need to make sure that your data is top-quality.

Data-driven decision-making (D3M) appears to be the new buzz phrase for this century, the information age. On the education front, teachers and administrators are engaging in data-centered dialog in grade-level meetings, lounges, hallways, and class-rooms as they brainstorm toward closing the gap in student achievement. Clearly, such discussion among professional educators has dramatically increased since the enactment of the No Child Left Behind Act of 2001. And as a result of NCLB, the teaching community is establishing data repositories to analyze information to improve teaching and learning within the school environment. In addition, business organizations specializing in data collection, analysis, and technology reporting are rapidly emerging in large numbers to assist schools as they struggle to meet state, federal, and local requirements. Many software vendors, in fact, now serve the education market through their development of disaggregation products—those specifically designed to help schools meet their goals and close the gap in student achieve-ment via D3M.

Using a Data Repository
Of course, data collection within schools and toward the improvement of teaching and learning is not a new practice. Schools have been collecting, analyzing, and reporting data manually to local, state, and federal agencies for many years. Over time, and within the personnel pool of most schools, technically skilled employees have played a customary role in developing electronic spreadsheets and databases to meet data’s increasing demand. Yet, as this demand continues to grow, increasingly greater sophistication in data analysis—necessitating highly qualified database personnel and systems—is also expected on an ongoing basis. No longer is large-scale data analysis conducted with database software such as Excel (www.microsoft.com), File Maker Pro (

www.filemaker.com), or similar spreadsheet programs. Instead, robust “relational” database systems, such as Microsoft SQL or Oracle engines (www.oracle.com), are now used to manipulate such data. After immeasurable hours have been invested in the manual “crunching” of numbers, new technologies have minimized the burden of educational reporting. Technology has assumed the role of managing data, freeing teachers and administrators to focus on making decisions drawn from the data. The influx of relational database management systems (RDBMSs), data warehousing (DW) strategies, and procedures based upon the Schools Interoperability Framework (SIF) repository model is generating a knowledge base, or pool of data-analysis experts,that is significantly influencing the decision-making of school administrators as they review the multiple measures now available to them. But before any decision can be made with regard to developing or purchasing a RDBMS, incorporating a DW strategy, or even considering basing an important decision on a SIF repository model, schools and districts must have procedures in place for ensuring quality data.