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Integrating Big Data Processing tools with Predictive Modeling and Visualization with Tableau Desktop
Updated on Sep, 2026
Programming, Data Science, Big Data
Duration - 4.5 hours
Training 5 or more people ?
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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, 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 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 PySpark
You will learn machine learning with geospatial data using the Spark MLlib library
You will learn data analysis using PySpark, MongoDB, and Tableau
You will learn how to manipulate, clean, and transform data using PySpark data frames
You will learn how to create Geo Maps in Tableau Desktop
You will also learn how to create dashboards in Tableau Desktop
Tableau Data Visualization
Data Transformation and Manipulation
Big Data Machine Learning
Geo Mapping with Tableau
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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