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.
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You will learn how to create data processing pipelines using PySpark
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You will learn machine learning with geospatial data using the Spark MLlib library
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You will learn data analysis using PySpark, MongoDB and Power BI
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You will learn how to manipulate, clean and transform data using PySpark dataframes
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You will learn how to create Geo Maps using ArcMaps for Power BI
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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
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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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