WENDELIN combines Scikit Learn machine learning and NEO distributed storage for out-of-core data analytics in python
Table of Contents
In this lecture we learn how to industrialise data science with wendelin.
We describe the process of ingesting, storing, processing and visualising 2 types of data in Data Lake using 2 different tools
We will discuss each step in details in following tutorials.
Batch Transfer to Data Lake
First we will learn how to use embulk to transfer batch data to wendelin.
Embulk has many input plugins to get data from all kinds of data sources, here we use an example of transferring data from mongodb.
Buffered Streaming to Data lake
Next we will learn how to use Fluentd to transfer streaming data to wendelin.
Once we have data in our Data Lake we will show how to manipulate data.
As the final step we will show to visualise data using notebooks with plotly chart editor.