BIG Data & Hadoop Applications in Sports

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Applications of BIG Data in Sports


Introduction to Big Data

Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications

Systems / Enterprises generate huge amount of data from Terabytes to Petabytes

Understanding Big Data can give you innovative solutions to various queries.


Applications of BIG Data in Sports

• Game Day Analysis• Player Auctions• Sports Broadcasting• Fitness Management


BIG Data Applications in Sports

Game Day Analysis

Like other businesses, sports teams strive to make better decisions faster. Coaching staff are leveraging analytics to better understand performance of their own teams as well that of the opposition. For example, NFL teams utilize Big Data to get real-time analytics regarding player & strategy performance. Based on this, they instantly alter their tactics. Big Data is also extensively utilized in sports such as Football, Rugby, Formula 1 and Basketball. Additionally, all plays are recorded, time stamped and tagged with metadata to allow coaches and players to analyze their performance.

Get Started with BIG Data & Hadoop

Player Auctions

Data has become a key negotiation tool in player auctions & transfers. For example, each team can assign specific qualities to their player requirement based on which they get instant transfer recommendations. Nowadays, even players have begun to use data as a bargaining tool in contract negotiations as it helps them to quantify their abilities & contributions.

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BIG Data Applications in Sports


Fitness Management

Wearable technology has revolutionized player activity monitoring. It goes beyond monitoring stamina & performance to tracking muscle strength, internal health & body compositions. This ensures the coaching staff can create customized conditioning programs to maximize player well-being. For example adidas’ miCoach, a wearable device uses a collection of sensors that sense heart rate and other vitals. It consists of a tri-axis accelerometer, GPS, magnetometer and gyroscope to track player movements.

Sports Broadcasting

The use of Big Data is prominent in every sport you watch, from gathering information about which way would a ball swing in a cricket match by analyzing where the ball bounced, the bowlers hand action, speed etc. to analyzing live tweets and displaying the same on the screen. Sports broadcasters have cracked the code for immersive viewing. Turner Broadcasting System Inc.’s has admitted that they are forced to “future proof” the company by using Big Data to analyze consumers’ viewing habits.



Current Examples of Big Data Application

Infiniti Red Bull Racing Formula one is one of the most popular sports in the world, and one of the most data driven. Red Bull racing rely

on real-time information to make enhancement to cars and in race strategies. Every lap driven by the F1 car, 100 sensors produce enough data like tire pressure, tire temperature, suspension performance, wheel alignment and whole lot of engine statistics, the pit team uses that data to make immediate decisions.

Zebra Technologies The company makes Radio Frequency Identification tags, as part of their Motionworks Sports Solution, that

attach to equipment, balls and players to track movement, distance and speed. The tags blink 25 times per second and deliver data in 120 milliseconds. This data is used to analyze in the post match session to understand what worked and what didn’t work for the teams.

Sports UV The Company has six cameras in each NBA arena that collect data on the movements on every player and

movements of the basketball 25 times per second. This data is used by game developers to understand ball movements and incorporate them. Get Started with BIG Data & Hadoop


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How Are Insights Derived from BIG Data?

Say Hello to Hadoop Development :)




Introduction to Hadoop

Apache Hadoop is a framework that allows the distributed processing of large data sets across clusters of commodity computers using a simple programming model.

It is an Open-Source Data Management technology with extensive storage and distributed processing.

Hadoop CharacteristicsFlexible

Reliable

Economical

Scalable Get Started with BIG Data & Hadoop



Why Should You Learn Hadoop?

• Hadoop is a modern BIG Data processing framework which utilizes distributed computing clusters.

• It can process, manage and store unstructured data with absolute ease.

• Due to its scalability & effectiveness, companies are heavily adopting Hadoop.

• It has become the standard for storing, processing and analyzing big data.

• BIG Data & Hadoop professionals are in extremely high demand.

• This is the first step to becoming a data scientist or data architect.




Reports – 2015

Here are some of the other Reports that convey the same message:

• “It is expected that Hadoop and Big Data Analytics will grow to around $13.9 billion from 2012 to 2017.” (Markets and Markets Research Report)

• “The Data market currently with the fastest growth are Hadoop and NoSQL software and services.” (Technology Research Organization, Wikibon)

• “The Big Data market will likely hit $23.8 billion with a 31.7% rise per year.” (IDC Report)

• “Almost 90% organizations have embarked on Hadoop related projects and thus Hadoop skills are in huge demand.” (According to the Big Data Executive Survey 2013)

• “Companies hiring Hadoop professionals Analytics professionals obtain a 250 percent hike in their salaries.” (According to Analytics Industry Report)

Gartner had predicted, “Hadoop will be in most advanced analytics products by 2015.” By far and large, this prediction has turned out to be true. Hadoop is “The Technology” to harness Big Data




Predictions for 2015

According to the Forrester Report:

• A new data economy will arise, Hadooponomics. Due to its vast data prowess, enterprise adoption of Hadoop will become compulsory. All those companies, which were unsure of adopting Hadoop till 2014, are bound to adopt it in 2015

• The surge in demand for Hadoop job professionals will be fulfilled by Java professionals & other software engineers who will upgrade their skills

• The creation of SQL-on-Hadoop options will further enhance usability & adoption

• Due to the introduction of Yarn (Version 2.0), the usage of Hadoop will go beyond analytics. It will transform into an application platform giving birth to new frameworks in the Hadoop ecosystem

• New Hadoop sources will emerge from organizations like Oracle, HP, Tibco and SAP. Vendors such as Red Hat, VMware and Microsoft will include Hadoop in their operating Systems




Why SkillSpeed?

Course Curriculum

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Instructor Led Live Virtual Sessions

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Content via LMS

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Course Topics

Module 1

Introduction to Big Data and Hadoop

Module 2

HDFS Internals, Hadoop

Configurations and Data Loading

Module 3

Introduction to Map Reduce

Module 4

Advanced Map Reduce Concepts

Module 5

Introduction to Pig

Module 6

Advanced Pig and Introduction to Hive

Module 7

Advanced Hive Concepts

Module 8

Extending Hive and HBase Introduction

Module 9

Advanced HBase and Oozie Introduction

Module 10

Project Set-up Discussion




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BIG Data & Hadoop Applications in Sports

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