Olympic Games Analytics Project in Apache Spark for Beginner
Olympic Games Analytics Project in Apache Spark for beginner using Databricks (Unofficial)
Updated on Jun, 2025
Language - English
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.
Curriculum
Check out the detailed breakdown of what’s inside the course
Apache Spark Project
24 Lectures
-
Introduction
02:54
02:54
-
Download Resources
-
File level details
00:39
00:39
-
(Old) Free Account creation in Databricks
01:51
01:51
-
(New) Free Account Creation in Databricks
01:50
01:50
-
Importing Databricks Notebook
01:54
01:54
-
Overview and Project Objective
01:54
01:54
-
File Content Explaination
01:50
01:50
-
Launch Spark Cluster
02:14
02:14
-
Spark Notebook Basics
05:18
05:18
-
Loading data into Spark Dataframe
15:50
15:50
-
Distribution of the age of gold medalists
04:04
04:04
-
Gold Medals for Athletes Over 50 based on Sports
02:09
02:09
-
Women medals per edition(Summer Season) of the Games
02:19
02:19
-
Top 5 Gold Medal Countries
02:46
02:46
-
Disciplines with the greatest number of Gold Medals
01:40
01:40
-
Height vs Weight of Olympic Medalists
01:52
01:52
-
Variation of Male/Female Athletes over time
01:59
01:59
-
Variation of (Age/Weight/Height) for Male/Female Athletes over time
03:09
03:09
-
Weight over year for Male/Female Gymnasts
02:18
02:18
-
Weight/Height over years for Male/Female Lifters
01:39
01:39
-
Gold/Silver/Bronze Medals based on Countries
04:56
04:56
-
Publish Notebook to the Web
01:26
01:26
-
Thank you
00:20
00:20
Instructor Details
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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