The data sgp is an archive of data that can be accessed by researchers at a variety of universities and observatories worldwide. The data is used to study a number of specific research questions in Earth history, and the end goal is to migrate it into permanent data repositories. This will allow researchers to utilize the information in new ways, and the access will be much easier than accessing the metadata and legacy data on a individual basis.
The sgpData package contains 4 examplar data sets for use with Student Growth Percentile (SGP) analyses. The first, sgpData_WIDE, specifies the format for data to be used with the lower level SGP functions studentGrowthPercentiles and studentGrowthProjections. The second, sgpData_LONG, specifies the format for data to be utilized by higher level functions such as abcSGP, prepareSGP, and analyzeSGP. The third, sgpData_INSTRUCTOR_NUMBER, is an anonymized teacher-student lookup table used to produce teacher level aggregates.
In SGP analysis, students are compared to their academic peers to determine how much they have grown on an assessment versus other students taking the same test. Teachers can use SGP scores to quickly determine if a student has demonstrated more or less relative growth than their peers, and they are also useful for monitoring student progress in a given period of time. SGP scores are available in two formats: Window Specific SGP, which is based on district screening windows, and Current SGP, which provides a snapshot of a student’s growth.
Whether in the cloud or on premises, organizations have massive amounts of structured and unstructured data, spread across many different endpoints. Adding to this mix, employees often keep company-related data on their own personal devices, which contributes to the data sprawl problem. This proliferation of data can make it difficult to find what you need, and creates security risks when multiple versions of the same data exist in disparate locations. Data sprawl has become a significant concern for many companies, and there are a number of ways to help reduce the risk. One way is to implement a governance policy that addresses data management and access controls. Another is to consider implementing an advanced analytics platform such as SAS that can help you make sense of all the data and identify areas where improvements can be made. The platform can also help you identify potential opportunities to save money and improve business performance.