Spatial bi for analyzing school district diversity
Páginas: 2 (269 palabras)
Publicado: 25 de febrero de 2012
SPATIAL BI for analyzing School District Diversity by Gustavo Zarrate
Current situations in School Districts acrros USA are demanding a deep analysis in demographicschanges in order to prevent racial identified schools forbidden by law.
Our effort is to compile information for the last 5 years by census tracks, identify a districtdiversity signature and check how schools are compared with this district signature.
The first process is to manage the possibility to identify each data directly to one student.A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Current situations in School Districts acrros USA are demanding adeep analysis in demographics changes in order to prevent racial identified schools forbidden by law.
Our effort is to compile information for the last 5 years by censustracks, identify a district diversity signature and check how schools are compared with this district signature.
The first process is to manage the possibility to identifyeach data directly to one student. A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Current situations in SchoolDistricts acrros USA are demanding a deep analysis in demographics changes in order to prevent racial identified schools forbidden by law.
Our effort is to compile informationfor the last 5 years by census tracks, identify a district diversity signature and check how schools are compared with this district signature.
The first process is to managethe possibility to identify each data directly to one student. A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Current situations in School Districts acrros USA are demanding a deep analysis in demographicschanges in order to prevent racial identified schools forbidden by law.
Our effort is to compile information for the last 5 years by census tracks, identify a districtdiversity signature and check how schools are compared with this district signature.
The first process is to manage the possibility to identify each data directly to one student.A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Current situations in School Districts acrros USA are demanding adeep analysis in demographics changes in order to prevent racial identified schools forbidden by law.
Our effort is to compile information for the last 5 years by censustracks, identify a district diversity signature and check how schools are compared with this district signature.
The first process is to manage the possibility to identifyeach data directly to one student. A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Current situations in SchoolDistricts acrros USA are demanding a deep analysis in demographics changes in order to prevent racial identified schools forbidden by law.
Our effort is to compile informationfor the last 5 years by census tracks, identify a district diversity signature and check how schools are compared with this district signature.
The first process is to managethe possibility to identify each data directly to one student. A process to generate random identifiers is needed to generate anonymous input data for the analysis.
Leer documento completo
Regístrate para leer el documento completo.