Big Data Analytics with PySpark & PowerBI & MongoDB
Start creating a big data analytics pipeline, using big data technologies like PySpark, MLlib, Power BI and MongoDB.
Installing Python
Installing Apache Spark
Installing Java
FREE PREVIEWTesting Spark
Installing MongoDB
Installing NoSQL Booster
Integrating PySpark with Jupyter Notebook
Extracting the Data Used in this Course
Transforming the Data
Loading the Data in MongoDB
Data Pre-Processing and Preparation
Building the Machine Learning Model
Creating the Prediction Dataset
Installing Visual Studio Code
Building the ETL Pipeline Script
Building the ML Pipeline Script
Installing PowerBI Desktop
Installing Mongo ODBC Drivers
Creating System DSN for MongoDB
Loading Data into PowerBI
Visualizing an Earthquake Prediction Map
Creating Table Plots
Plotting Maximum and Average Magnitude Values
Creating Bar Chart of Earthquake Occurence
Creating Doughnut Charts
PySpark Data Pipeline
PySpark Power BI
Commands
€10,00
Regular price
How to create big data processing pipelines using PySpark.
Machine learning with geospatial data using the Spark MLlib library.
Data analysis using PySpark, MongoDB and Power BI.
How to manipulate, clean and transform data using PySpark dataframes.
How to create Geo Maps using ArcMaps for Power BI.
How to create dashboards in Power BI.
Data Scientists at any level
GIS Developers at any level
Machine Learning engineers at any level
Undergraduate students
Master students and PhD candidates
Researchers and Academics
Professionals and Companies