Big Data Analytics with PySpark + Tableau Desktop + MongoDB

Integrating Big Data Processing tools with Predictive Modeling and Visualization with Tableau Desktop

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Last Updated: 2023-03-20 04:03:37 English Course Type: Self Learning

Tableau Data Visualization
PySpark Programming
Data Analysis
Data Transformation and Manipulation
Big Data Machine Learning
Geo Mapping with Tableau
Geospatial Machine Learning
Creating Dashboards

Welcome to the Big Data Analytics with PySpark + Tableau Desktop + MongoDB course. In this course we will be creating a big data analytics solution using big data technologies like PySpark for ETL, MLlib for Machine Learning as well as Tableau for Data Visualization and for building Dashboards.

We will be working with earthquake data, that we will transform into summary tables. We will then use these tables to train predictive models and predict future earthquakes. We will then analyze the data by building reports and dashboards in Tableau Desktop.

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.

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 data processing pipelines using PySpark
You will learn machine learning with geospatial data using the Spark MLlib library
You will learn data analysis using PySpark, MongoDB and Tableau
You will learn how to manipulate, clean and transform data using PySpark dataframes
You will learn how to create Geo Maps in Tableau Desktop
You will also learn how to create dashboards in Tableau Desktop

Basic Understanding of Python
Little or no understanding of GIS
Basic understanding of Programming concepts
Basic understanding of Data
Basic understanding of what Machine Learning is

Python 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

Section 1 : Introduction 1 Lectures 00:00:00
Lecture 1 :
Introduction Preview
Section 2 : Setup and Installations 6 Lectures 00:00:00
Lecture 1 :
Python Installation
Lecture 2 :
Installing Apache Spark
Lecture 3 :
Installing Java (Optional)
Lecture 4 :
Testing Apache Spark Installation
Lecture 5 :
Installing MongoDB
Lecture 6 :
Installing NoSQL Booster for MongoDB
Section 3 : Data Processing with PySpark and MongoDB 4 Lectures 00:00:00
Lecture 1 :
Integrating PySpark with Jupyter Notebook
Lecture 2 :
Data Extraction
Lecture 3 :
Data Transformation
Lecture 4 :
Loading Data into MongoDB
Section 4 : Machine Learning with PySpark and MongoDB 3 Lectures 00:00:00
Lecture 1 :
Data Pre-processing
Lecture 2 :
Building the Predictive Model
Lecture 3 :
Creating the Prediction Dataset
Section 5 : Building the Data Pipeline Scripts 3 Lectures 00:00:00
Lecture 1 :
Installing Visual Studio Code
Lecture 2 :
Creating the PySpark ETL Script
Lecture 3 :
Creating the Machine Learning Script
Section 6 : Tableau Data Visualization 9 Lectures 00:00:00
Lecture 1 :
Installing Tableau
Lecture 2 :
Installing MongoDB ODBC Drivers
Lecture 3 :
Creating a System DSN for MongoDB
Lecture 4 :
Loading the Data Sources
Lecture 5 :
Creating a Geo Map
Lecture 6 :
Creating a Bar Chart
Lecture 7 :
Creating a Magnitude Chart
Lecture 8 :
Creating a Table Plot
Lecture 9 :
Creating a Dashboard
Section 7 : Source Code and Notebook 1 Lectures
Lecture 1 :
Source Code and Notebook

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