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Building Big Data Pipelines With Sparkr & Powerbi & Mongodb

Last updated 7/2020MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.29 GB | Duration: 3h 22m


 

RSpark and MongoDB for Big Data Processing and Predictive Modeling including Visualization with PowerBI Desktop

What you'll learn

SparkR Programming

Big Data Tools for R

Power BI Data Visualization

Data Analysis

Big Data Machine Learning

Geo Mapping with Power BI

Geospatial Machine Learning

Building Dashboards

Requirements

Basic Understanding of R Programming

Little or no understanding of GIS

Basic understanding of Programming concepts

Basic understanding of Data

Basic understanding of what Machine Learning is

Description

Welcome to the Building Big Data Pipelines with SparkR & PowerBI & MongoDB 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.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.SparkR is an R package that provides a light-weight frontend to use Apache Spark from R. SparkR provides a distributed data frame implementation that supports operations like selection, filtering, aggregation etc. (similar to R data frames, dplyr) but on large datasets. SparkR also supports distributed machine learning using MLlib.MongoDB is a document-oriented NoSQL database, used for high volume data storage. It stores data in JSON like format called documents, and does not use row/column tables. The document model maps to the objects in your application code, making the data easy to work with.You will learn how to create big data processing pipelines using R and MongoDBYou will learn machine learning with geospatial data using the SparkR and the MLlib libraryYou will learn data analysis using SparkR, R and PowerBIYou will learn how to manipulate, clean and transform data using Spark dataframesYou will learn how to create Geo Maps in PowerBI DesktopYou will also learn how to create dashboards in PowerBI Desktop

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Setup and Installations

Lecture 2 R Installation

Lecture 3 Installing Apache Spark

Lecture 4 Installing Java (Optional)

Lecture 5 Testing Apache Spark Installation

Lecture 6 Installing MongoDB

Lecture 7 Installing NoSQL Booster for MongoDB

Lecture 8 Installing SparkR

Lecture 9 Configuring SparkR

Section 3: Building the Big Data ETL Pipeline with SparkR

Lecture 10 Data Extraction

Lecture 11 Data Transformation 1

Lecture 12 Data Transformation 2

Lecture 13 Data Exporting

Section 4: Big Data Machine Learning with SparkR and MLlib

Lecture 14 Data Pre-processing

Lecture 15 Building the Predictive Model

Lecture 16 Creating the Prediction Dataset

Section 5: Data Visualization with Power BI

Lecture 17 Installing Power BI Desktop

Lecture 18 Installing MongoDB ODBC Drivers

Lecture 19 Creating a System DSN for MongoDB

Lecture 20 Loading the Data Sources

Lecture 21 Creating a Geo Map

Lecture 22 Creating a Donut Chart

Lecture 23 Creating a Area Chart

Lecture 24 Creating a Stacked Bar Chart

Section 6: Project Source Code

Lecture 25 Source Code

R Developers at any level,Data Eeers at any level,Developers at any level,Machine Learning eeers at any level,Data Scientists at any level,GIS Developers at any level,The curious mind

HomePage:

https://www.udemy.com/course/building-big-data-pipelines-with-sparkr-powerbi-mongodb/

 

 

 


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