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Big Data Analytics with Predictive Modeling and Visualization with Power BI Desktop
Updated on Sep, 2026
Programming, Database and Design Development, MongoDB
Duration - 3.5 hours
Training 5 or more people ?
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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 BI, and MongoDB.
We will be working with earthquake data, which 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.
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 Power BI
You will learn how to manipulate, clean and transform data using PySpark dataframes
You will learn how to create Geo Maps using Arc Maps for Power BI
You will also learn how to create dashboards in Power BI
Who this course is for:
Power BI Data Visualization
Data Transformation and Manipulation
Big Data Machine Learning
Geo Mapping with ArcMaps for Power BI
Geospatial Machine Learning
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
Check out the detailed breakdown of what’s inside the course
Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development.
Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.
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