to increase by 100x the impact of data science in your organization? Data Scientist Business Analysts Jupyter Users Est. 3-6 million Excel Users Est. 750 Million
analysts are being left out of the data science revolution 5 Big Data & ETL Interactive Data Visualizations Machine Learning Statistics and Advanced Analytics
Big Data analytics Head node Compute nodes Jupyter notebook Interactive Data Visualizations Machine Learning Predictions Extract, transform and query data
Code” Data Science Example 1 2 Select Anaconda Fusion Notebook and click “Upload” Select function you wish to run Click “Run” Data is loaded into spreadsheet 3 4
Extract data - pull data directly into Excel to perform analysis • Machine Learning – use trained models created by Data Scientists and plug them into your spreadsheet data • Interactive Visualizations – create custom advanced interactive graphs, charts and plots from Excel data • Big Data – analyze, transform, model and query data stored in Hadoop and Spark Figure: Anaconda Fusion on Mac Anaconda Fusion use cases
OSS – base of most successful modern software • Maturity – long history • Diversity • 100s of projects • 1000s of contributors • Vision • Jupyterlab • Community & Support • Popularity Jupyter as a Platform
The jupyter ecosystem • https://github.com/jupyter • https://github.com/jupyterlab • https://github.com/phosphorjs • Great community/support • Very pluggable* • Perfect for our use case • I.e.: why can’t excel have ML? • i.e.: why can’t excel do things that numpy/pandas do? • i.e.: we need better graphics (ala bokeh ;) ) for a dashboard of our metrics in excel Jupyter As a Tech Choice