Data Science covers the complete workflow from defining a question, finding the most suitable data source, identifying the right tools and finally presenting the best possible answer in a clear, engaging manner. But it all starts with having access to the data.
Margriet will walk you through some examples of how to collect, store and access data in the Cloud with the use of different APIs:
Store Twitter and weather data in a NoSQL database (Cloudant) and enrich the data with sentiment using Watson
Collect and store daily weather observations
Access this data in a Jupyter notebook using Python, Pandas and Spark
Real time Twitter sentiment in a Jupyter notebook using the PixieDust package
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Data Science in the Cloud
Margriet Groenendijk is a Developer Advocate at IBM Cloud Data Services. Currently she is all about data from storing, cleaning, munging and analysing through to visualisation. All to create clear narratives and figures showing new insights from diverse data sources. She uses a range of tools for this, such as Cloudant, dashDB, Spark and Python notebooks.