Oracle OpenWorld and CodeOne 2018 are two co-located conferences that took place in October 2018. Some 2000 sessions presented by over 2500 presenters form the core of these conferences. Many details are known about each of the sessions and the speakers – from title, abstract, room (size), date and time, session slides, session type and key topics to first name, last name, Twitter handle, picture, company, job title and bio. 
A data set is available with all this information: https://github.com/lucasjellema/DataAnalytics–IntroductionDataWrangling-JupyterNotebooks/tree/master/CaseOfOracleOpenWorld2018/datawarehouse (JSON format, 37 MB).
The columns in this data set:
'abstract', 'attributevalues', 'catalog', 'code', 'event', 'eventCode', 'files', 'length', 'participants', 'sponsors', 'times', 'title', 'title_sort', 'type', 'oracle_speaker', 'file_flag', 'JavaOne Rockstar', 'Oracle ACE Director', 'Oracle Java Champion','Groundbreaker Ambassador', 'Intermediate', 'Beginner', 'Advanced', 'All', 'track', 'speaker_count', 'instance_count', 'room_capacity', 'room', 'day', 'time', 'session_timestamp'
This data set has been prepared from the Session Catalog backing API using two Jupyter Notebooks that implement API calls, data merging and some light weight data wrangling. If you are interested in all detailed steps and the raw (unwrangled) data, please look here:
- Jupyter Notebook to fetch raw data into dozens of JSON files (per session type, per conference): Jupyter Notebook in GitHub
- Jupyter Notebook to merge and wrangle all raw data into a single JSON file: Jupyter Notebook in GitHub
- Raw JSON data files: https://github.com/lucasjellema/DataAnalytics–IntroductionDataWrangling-JupyterNotebooks/tree/master/CaseOfOracleOpenWorld2018/datalake
- Prepared for Visualization: https://github.com/lucasjellema/DataAnalytics–IntroductionDataWrangling-JupyterNotebooks/tree/master/CaseOfOracleOpenWorld2018/datamart
Please let me know if you manage to extract interesting insights from this data.
Resources
Some initial explorations have been done on this data. See for example:
- Exploring Oracle OpenWorld 2018 Session Catalog on Oracle Analytics Cloud: https://technology.amis.nl/2019/01/24/first-steps-with-oracle-analytics-cloud-gather-explore-wrangle-visualize/
- Creating a Data Flow in Oracle Analytics Cloud for enriching Oracle OpenWorld session data with Geo Encoding to Map visualization of data – https://technology.amis.nl/2019/01/26/creating-a-data-flow-in-oracle-analytics-cloud-to-enriching-with-geo-encoding-to-map-visualization-of-data/
- Exploring Oracle OpenWorld 2018 Session Catalog with Oracle Analytics Cloud – Data Flow to produce a Date Value and Timeline to Visualize the time related data – https://technology.amis.nl/2019/01/29/oracle-analytics-cloud-data-flow-to-produce-a-date-value-and-timeline-to-visualize-the-time-related-data/
- Slides from Oracle Code Rome session (Turn Data into Value – Starting with Data Analytics on Oracle Cloud ): https://www.slideshare.net/lucasjellema/turn-data-into-business-value-starting-with-data-analytics-on-oracle-cloud-oracle-code-rome-april-2019
- Video from Oracle Code Rome: Turn Data into Business Value – Starting with Data Analytics on Oracle Cloud – https://youtu.be/IkfhudP2v7U?t=20880
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