Big Data Analytics With Pyspark + Tableau Desktop + Mongodb
Last updated 2/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.37 GB | Duration: 4h 18m
Last updated 2/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.37 GB | Duration: 4h 18m
Integrating Big Data Processing tools with Predictive Modeling and Visualization with Tableau Desktop
What you'll learn
Tableau Data Visualization
PySpark Programming
Data Analysis
Data Transformation and Manipulation
Big Data Machine Learning
Geo Mapping with Tableau
Geospatial Machine Learning
Creating Dashboards
Requirements
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
Description
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 PySparkYou will learn machine learning with geospatial data using the Spark MLlib libraryYou will learn data analysis using PySpark, MongoDB and TableauYou will learn how to manipulate, clean and transform data using PySpark dataframesYou will learn how to create Geo Maps in Tableau DesktopYou will also learn how to create dashboards in Tableau Desktop
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Setup and Installations
Lecture 2 Python 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
Section 3: Data Processing with PySpark and MongoDB
Lecture 8 Integrating PySpark with Jupyter Notebook
Lecture 9 Data Extraction
Lecture 10 Data Transformation
Lecture 11 Loading Data into MongoDB
Section 4: Machine Learning with PySpark and MLlib
Lecture 12 Data Pre-processing
Lecture 13 Building the Predictive Model
Lecture 14 Creating the Prediction Dataset
Section 5: Creating the Data Pipeline Scripts
Lecture 15 Installing Visual Studio Code
Lecture 16 Creating the PySpark ETL Script
Lecture 17 Creating the Machine Learning Script
Section 6: Tableau Data Visualization
Lecture 18 Installing Tableau
Lecture 19 Installing MongoDB ODBC Drivers
Lecture 20 Creating a System DSN for MongoDB
Lecture 21 Loading the Data Sources
Lecture 22 Creating a Geo Map
Lecture 23 Creating a Bar Chart
Lecture 24 Creating a Magnitude Chart
Lecture 25 Creating a Table Plot
Lecture 26 Creating a Dashboard
Section 7: Source Code and Notebook
Lecture 27 Source Code and Notebook
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