DrupalCon Vienna 2017: Powerful Data Science with Drupal and Jupyter
Ongoing significant advances in our ability to collect, process, analyze, and communicate complex data together with the Open Data initiative give us exciting new opportunities to demonstrate and improve the quality of government services, identify and manage crucial factors of success, and partner with developers everywhere through enriched APIs. This session will explore how we can use Drupal together with that rapidly growing Jupiter Notebook platform and extensions and services developed in languages such as Python and R for practical and accessible data science in government and beyond.
Key takeaways
1. There are continuous improvements in our and Drupal’s ability to collect, process, analyze, and communicate complex data that we can use.
2. We can extend our existing content management systems and web applications to use this enriched data through the Open Data initiative and languages such as Python and R.
3. Jupyter, along the thew Python and R languages, are relatively easy to learn and extend to benefit optimally from this enriched data.
Key takeaways
1. There are continuous improvements in our and Drupal’s ability to collect, process, analyze, and communicate complex data that we can use.
2. We can extend our existing content management systems and web applications to use this enriched data through the Open Data initiative and languages such as Python and R.
3. Jupyter, along the thew Python and R languages, are relatively easy to learn and extend to benefit optimally from this enriched data.