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Big Data Analytics with PySpark Power BI and MongoDB

4.7

(22 students)
Last updated:November 6, 2024
Language:English

Big Data Analytics with PySpark Power BI and MongoDB

4.7

(22 students)

Rated Excellent on

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Overview

The Big Data Analytics with PySpark, Power BI, and MongoDB course equips learners with the critical skills to analyze, visualize, and manage vast data sets effectively. Covering both fundamental and advanced topics, this course delves into using PySpark for processing large-scale data, Power BI for creating insightful visualizations, and MongoDB for handling NoSQL databases. You’ll learn how to harness data to inform decision-making, optimize operations, and extract actionable insights. The curriculum is designed to provide hands-on experience, empowering you to work with diverse datasets and manage data pipelines end-to-end. This course also emphasizes best practices in big data management, data governance, and security, preparing you to tackle real-world challenges in data analytics with confidence. By the end, you’ll be prepared for impactful roles in data-driven environments.

Learning Outcomes

By the end of this course, you will be able to:

  • Gain proficiency in PySpark for large-scale data processing.
  • Develop advanced skills in Power BI for data visualization.
  • Understand MongoDB fundamentals and NoSQL database management.
  • Learn to create end-to-end data pipelines.
  • Master data governance and security best practices.
  • Apply data analytics techniques to solve complex problems.
  • Acquire the skills to make data-driven decisions.

How will I get my certificate?

You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.

Who is This course for?

This course is designed for aspiring data analysts, data engineers, and IT professionals who want to specialize in big data analytics. It’s ideal for those aiming to enhance their skills in data visualization, data processing, and database management with a focus on large-scale datasets.

Requirements

Basic knowledge of Python and SQL is recommended. Familiarity with data analysis concepts and prior experience with Excel or other spreadsheet tools will be beneficial. An understanding of database management and visualization techniques is helpful but not required, as foundational topics are covered in this course.

Career Path

    • Data Analyst
    • Big Data Engineer
    • Data Visualization Specialist
    • Business Intelligence Developer
    • Data Scientist
     

Course Curriculum

  • 6 sections
  • 26 lectures
  • 3 hours, 55 minutes total length
Expand all sections
  • video Introduction
    00:10:00

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This course includes:

  • Duration:
    3 hours, 55 minutes
  • Access:
    1 year access
  • Units:
    26
  • Level:
    Intermediate
  • CPD Points:
    10
  • Certificate:
    Yes