Load Your Data Into a Jupyter Notebook
You’ve heard all the flashy statistics about big data, like how every day more than 2.5 quintillion bytes of data is created and that more data has been created in the last two years alone than every previous year combined (IBM). Here’s another one to add to the list: 99.5% of newly created data is never analyzed (MIT).
Only half a percent of all that data created ever makes it out of its storage warehouse. But these two new notebooks are here to help! They provide code snippets to load data from some of the most popular storage mediums into a Jupyter notebook. Then you’re free to analyze all that data with the IBM Bluemix Spark service and start cutting into that 99.5%.
These notebooks, one for each Python and Scala, show how you can access Bluemix Object Storage, DashDB, Cloudant, PostgreSQL and MongoDB (Python only) databases. The snippets can be inserted directly into your notebooks and include instructions on how to get your data into the notebook environment.