Welcome to the Building Big Data Pipelines with R & Sparklyr & PowerBI 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, 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.Power BI Desktop is a powerful data visualization tool that lets you build advanced queries, models and reports. With Power BI Desktop, you can connect to multiple data sources and combine them into a data model. This data model lets you build visuals, and dashboards that you can share as reports with other people in your organization.
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 Power BI
● You will learn how to manipulate, clean and transform data using Spark dataframes
● You will learn how to create Geo Maps in Power BI Desktop
● You will also learn how to create dashboards in Power BI Desktop

WHAT YOU WILL LEARN
● Power BI Data Visualization
● R Programming
● Data Analysis
● Big Data Machine Learning
● Geo Mapping with ArcGIS Maps for Power BI
● Geospatial Machine Learning
● Creating Dashboards

WHO THIS COURSE IS FOR
● R Developers at any level
● Data Engineers at any level
● Developers at any level
● Machine Learning engineers at any level
● Data Scientists at any level
● GIS Developers at any level
● The curious mind

1. Introduction
2. Setup and Installations
3. Building the Big Data ETL Pipeline with Sparklyr
4. Big Data Machine Learning with Sparklyr
5. Data Visualization with Power BI
6. Project Sources Code

Edwin Bomela is a Big Data Engineer and Consultant, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development. He is currently a consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.