Data Warehousing: An Aid to Decision-Making.

IN EDUCATION, WE ARE CONSTANTLY looking for the magic bullet--that intervention which will miraculously result in higher achievement scores for our students, happier and more productive teachers, etc. The pressure for improvement has caused education to become a "bandwagon" industry. Therefore, educational leaders adopt the latest fad in hopes that it will bring them to the promised land with little or no budget increase. This has been referred to as the LYNT-TYNT-NYNT Syndrome, which translates into Last Year's New Thing -This Year's New Thing-Next Year's New Thing (Markowitz and Elovitz 2001). All too often these "new things" represent a decision-maker's interest, and bear little if any connection to the programs of previous years or to the educational needs of the school or district. However, with the advent of No Child Left Behind and the public's demand for greater accountability, this is no longer acceptable. Thus, the answer lies in the ability of educational leaders to collect, store, analyze and effectively utilize large amounts of data to inform their decision-making. This is where data warehousing can help. Hart and Kamber (2001) define a data warehouse as "a repository of information collected from multiple sources, stored under a unified scheme, and which usually resides at a single site." In educational terms, all past information available in electronic format about a school or district such as budget, payroll, student achievement and demographics is stored in one location where it can be accessed using a single set of inquiry tools. Two factors make this process different from a typical data processing environment in a school or district. First, while the data warehouse contains historical information, it does not contain current-year information. Using current-year data is not recommended because it has not been cleansed to eliminate incompatibilities. Also, true data mining is computer intensive and usually not conducted in a day-to-day production environment. A second difference is that information from the various databases is extracted and then interrelated to ensure compatibility for ease of analysis. Databases are found in the normal school environment; however, they exist as separate entities, often in different computer languages that require the knowledge of various types of report-generating software. In a data warehouse, the integration of the information from these databases allows new queries (questions) to be investigated. For example, when a district adopts a new textbook series, a properly constructed data warehouse makes it possible to compare the impact of that purchase on achievement with relative ease. Generally, the information about the purchase and student achievement would be stored in existing but separate databases. After the required information is passed to the data warehouse, it can be extracted using a simple set of inquiry tools. Using the same warehouse, a historical comparison of success on standardized tests can be disaggregated by grade, race, sex or teacher. This potential for extracting information is amazing. The appeal of this process is that decisions could be based upon facts rather than suppositions, dubious beliefs or even rumors that have formed the basis for many past administrative decisions. The concept of data-driven decision-making is as simple as it sounds. Collecting data, refining the data into a usable format, and basing decisions on the information is the essential concept. Historically, collecting data has not been hard to accomplish in schools. …