Building Big Data Pipelines with R & Sparklyr & Tableau

Welcome to the Building Big Data Pipelines with R & Sparklyr & Tableau course. In this course we will be creating a big data analytics solution using big data technologies for R. In our use case we will be working with raw earthquake data and  we will be applying big data processing techniques to extract transform and load the data into usable datasets. Once we have processed and cleaned the data, we will use it as a data source for building predictive analytics and visualizations. Tableau Desktop is a powerful data visualization tool, used for big data analysis and visualization. It allows for data blending, real-time analysis and collaboration of data. No programming is needed for Tableau Desktop, which makes it a very easy and powerful tool to create dashboards apps and reports. Sparklyr is an open-source library that is used for processing big data in R, by providing an interface between R and Apache Spark. It allows you to take advantage of Spark's ability to process and analyze large datasets in a distributed and interactive manner. It also provides interfaces to Spark's distributed machine learning algorithms and much more. - You will learn how to create big data processing pipelines using R - You will learn machine learning with geospatial data using the Sparklyr library - You will learn data analysis using Sparklyr, R and Tableau - You will learn how to manipulate, clean and transform data using Spark dataframes - You will learn how to create Geo Maps in Tableau Desktop - You will also learn how to create dashboards in Tableau Desktop