Learn how a K-12 school district in Southern California analyzed new data points collected during remote learning in school year 2021 using T-SQL and Jupyter notebook on Jovian.ml. Discover what insights were gained from confidential student data.
Year 2020 has been a challenging year. On March 13, 2020, all public schools in California were shut down due to COVID-19. All students ended their 2020 school year in a remote learning setting. Early August, all students had to start school year 2021 remotely still. I work in a school district as a Database Manager in Southern California. Our school district is a K-12 school district and have roughly 50,000 students and 50 schools. I work in Information Technology department and my main role is to maintain and support data in any information system that school district is using. Because of school closures since March this year, a lot of changes in the systems were made because students can physically go to schools to get instructions. Because of these changes, we were able to collect some new data points this school year to analyze. It is interesting to see what these new data points can tell us.
As a first step, let's upload our Jupyter notebook to Jovian.ml.
project_name = "analyzing-k12-student-data-2021" # change this
!pip install jovian --upgrade -q
[jovian] Attempting to save notebook.. [jovian] Please enter your API key ( from https://jovian.ml/ ): API KEY: ········ [jovian] Updating notebook "yinyinw/analyzing-k12-student-data-2021" on https://jovian.ml/ [jovian] Uploading notebook.. [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ml/yinyinw/analyzing-k12-student-data-2021