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Olympic Games Analytics Project in Apache Spark for Beginner

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Olympic Games Analytics Project in Apache Spark for Beginner

Olympic Games Analytics Project in Apache Spark for beginner using Databricks (Unofficial)

updated on icon Updated on Jun, 2025

language icon Language - English

person icon Bigdata Engineer

English [CC]

category icon Development ,Database and Design Development,

Lectures -25

Resources -3

Duration -1 hours

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Course Description

In this course, you will learn to Analyze data (Olympic Game) in Apache Spark using Databricks Notebook (Community edition), 

  • Basics flow of data in Apache Spark, loading data, and working with data, this course shows you how Apache Spark is perfect for a Big Data Analysis job. 
  • Learn the basics of Databricks notebook by enrolling on the Free Community Edition Server.
  • Olympic Games Analytics is a real-world example. 
  • Graphical  Representation of Data using Databricks notebook.
  • Hands-on learning.
  • Real-time Use Case.
  • Publish the Project on the Web to Impress your recruiter.

About Databricks: 

Databricks lets you start writing Spark queries instantly so you can focus on your data problems. Let's discover more about the Olympic Games using Apache Spark.

Data:

Data exploration about the recent history of the Olympic Games. We will explore a dataset on the modern Olympic Games, including all the Games from Athens 1896 to Rio 2016.

Goals

  • In this course, you will learn to Analyze data (Olympic Game) in Apache Spark using Databricks Notebook (Community edition).
  • Data exploration about the recent history of the Olympic Games using Apache Spark.
  • Basics flow of data in Apache Spark, loading data, and working with data, this course shows you how Apache Spark is perfect for a Big Data Analysis job.
  • Learn the basics of Databricks notebook by enrolling on the Free Community Edition Server.
  • Olympic Games Analytics is a real-world example.
  • Graphical  Representation of Data using Databricks notebook.
  • Transform structured data using SparkSQL and DataFrames.
  • Publish the Project on the Web to Impress your recruiter.

Prerequisites

  • Apache Spark basic fundamental knowledge is required and SQL Basics.

Following browsers on Windows and macOS desktops:

  • Google Chrome (Latest version), Firefox (Latest version), Safari (Latest version), Microsoft Edge* (Latest version).
  • Internet Explorer 11* on Windows 7, 8, or 10 (with the latest Windows updates applied).
  • *You might see performance degradation for some features on Microsoft Edge and Internet Explorer.

The following browsers are not supported:

  • Mobile browsers.
  • Beta, “preview,” or otherwise pre-release versions of desktop browsers.
Olympic Games Analytics Project in Apache Spark for Beginner

Curriculum

Check out the detailed breakdown of what’s inside the course

Apache Spark Project

24 Lectures
  • play icon Introduction 02:54 02:54
  • play icon Download Resources
  • play icon File level details 00:39 00:39
  • play icon (Old) Free Account creation in Databricks 01:51 01:51
  • play icon (New) Free Account Creation in Databricks 01:50 01:50
  • play icon Importing Databricks Notebook 01:54 01:54
  • play icon Overview and Project Objective 01:54 01:54
  • play icon File Content Explaination 01:50 01:50
  • play icon Launch Spark Cluster 02:14 02:14
  • play icon Spark Notebook Basics 05:18 05:18
  • play icon Loading data into Spark Dataframe 15:50 15:50
  • play icon Distribution of the age of gold medalists 04:04 04:04
  • play icon Gold Medals for Athletes Over 50 based on Sports 02:09 02:09
  • play icon Women medals per edition(Summer Season) of the Games 02:19 02:19
  • play icon Top 5 Gold Medal Countries 02:46 02:46
  • play icon Disciplines with the greatest number of Gold Medals 01:40 01:40
  • play icon Height vs Weight of Olympic Medalists 01:52 01:52
  • play icon Variation of Male/Female Athletes over time 01:59 01:59
  • play icon Variation of (Age/Weight/Height) for Male/Female Athletes over time 03:09 03:09
  • play icon Weight over year for Male/Female Gymnasts 02:18 02:18
  • play icon Weight/Height over years for Male/Female Lifters 01:39 01:39
  • play icon Gold/Silver/Bronze Medals based on Countries 04:56 04:56
  • play icon Publish Notebook to the Web 01:26 01:26
  • play icon Thank you 00:20 00:20

Instructor Details

Bigdata Engineer

Bigdata Engineer

I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes

My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.

Responsibilities includes,

- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices

I am sure the knowledge in these courses can give you extra power to win in life.

All the best!!

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