Big Data Analytics with PySpark + Power BI + MongoDB

Big Data Analytics with PySpark + Power BI + MongoDB, available at $54.99, has an average rating of 4.15, with 27 lectures, based on 19 reviews, and has 129 subscribers.

You will learn about Power BI Data Visualization PySpark Programming Data Analysis Data Transformation and Manipulation Big Data Machine Learning Geo Mapping with ArcMaps for Power BI Geospatial Machine Learning Creating Dashboards This course is ideal for individuals who are Python Developers at any level or Data Engineers at any level or Developers at any level or Machine Learning engineers at any level or Data Scientists at any level or GIS Developers at any level or The curious mind It is particularly useful for Python Developers at any level or Data Engineers at any level or Developers at any level or Machine Learning engineers at any level or Data Scientists at any level or GIS Developers at any level or The curious mind.

Enroll now: Big Data Analytics with PySpark + Power BI + MongoDB

Summary

Title: Big Data Analytics with PySpark + Power BI + MongoDB

Price: $54.99

Average Rating: 4.15

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: R799.99

Quality Status: approved

Status: Live

What You Will Learn

Power BI Data Visualization
PySpark Programming
Data Analysis
Data Transformation and Manipulation
Big Data Machine Learning
Geo Mapping with ArcMaps for Power BI
Geospatial Machine Learning
Creating Dashboards

Who Should Attend

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

Target Audiences

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

Welcome to the Big Data Analytics with PySpark + Power BI + MongoDB course. In this course we will be creating a big data analytics pipeline, using big data technologies like PySpark, MLlib, Power BIand MongoDB.

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 Power BI Desktop.

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.

MongoDBis a document-oriented NoSQLdatabase, 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 Power BI
You will learn how to manipulate, clean and transform data using PySpark dataframes
You will learn how to create Geo Maps using ArcMaps for Power BI
You will also learn how to create dashboards in Power BI

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Setup and Installations

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

Chapter 3: Data Processing with PySpark and MongoDB

Lecture 1: Integrating PySpark with Jupyter Notebook

Lecture 2: Data Extraction

Lecture 3: Data Transformation

Lecture 4: Loading Data into MongoDB

Chapter 4: Machine Learning with PySpark and MLlib

Lecture 1: Data Pre-processing

Lecture 2: Building the Predictive Model

Lecture 3: Creating the Prediction Dataset

Chapter 5: Creating the Data Pipeline Scripts

Lecture 1: Installing Visual Studio Code IDE

Lecture 2: Creating the PySpark ETL Script

Lecture 3: Creating the Machine Learning Script

Chapter 6: Power BI Data Visualization

Lecture 1: Installing Power BI Desktop

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 Table Plot

Lecture 7: Creating an Area Chart

Lecture 8: Creating a Bar Chart

Lecture 9: Creating a Doughnut Chart

Chapter 7: Source Code and Notebook

Lecture 1: Source Code and Notebook

Instructors

EBISYS R&D
Big Data Engineering

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 4 votes
4 stars: 7 votes
5 stars: 7 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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