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Building Big Data Pipelines with R & Sparklyr & Power BI

R for Big Data Processing and Predictive Modeling including Visualization with Power BI Desktop

     
  • 4.4
  •  |
  • Reviews ( 14 )
₹519

This Course Includes

  • iconudemy
  • icon4.4 (14 reviews )
  • icon2h 26m
  • iconenglish
  • iconOnline - Self Paced
  • iconprofessional certificate
  • iconUdemy

About Building Big Data Pipelines with R & Sparklyr & Power BI

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.