Bigdata

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data scientist.

Other make you mere big data developer.

What the world says :

The Technology

What is Big Data?

What Happens in an Internet Minute?

And Future Growth is Staggering

Today, the number of networked devices

the global population

By 2015,the number of networked devices

2X the global population

In 2015, it would take you 5 years

to view all video crossing IP networks each second

Data that is too big, moves too fast and exceeds the limits of traditional databases is called Big Data

90% of the data today has been created in last 2 years

An increasingly digitised world is generating humongous amount of data every second. And the sources are - Smartphones, IoT senors, Smart TVs, watches, Facebook, Twitter, Youtube, Manufacturing industry, Service industries, Retail, Banks, Insurance companies, digital pictures, transactions, GPS, traffic, sensors in vehicles and aircrafts, connected homes, healthcare etc

Everyday We Create 2.500,000,000,000,000,000
(2.5 Quintillion Bytes of Data)



This would fill 10 million Blu-ray discs, the height of which stcked, would mesaure the height of 4 Eiffel Towers on top of one another.

90% of the world’s data has been created in the last 2 years alone

Big Data market will grow to $80 billion from current $40 billion
Big Data and Analytics revenue is expected to grow to $187 billion

What is Analytics?


Analytics digs large amounts of data to uncover hidden patterns, correlations, and other insights. This information almost always tell something about the data sources which can be used to increase revenue, predict weather, save environment, save people, manage traffic, reduce accidents drastically, diagnose life threatening diseases, enhance customer service, calculate insurance premium based on eating habit or driving habit, genetics, etc.

Descriptive Analytics

What happened - Result

Diagnostic Analytics

Why did it happen - Causal

Predictive Analytics

What is likely to happen - Prediction

Prescriptive Analytics

What should I do about it - Prediction and Action

Why Big Data Analytics?

MOST DISRUPTIVE TECHNOLOGY OF FUTURE


  • Generation of unstructured data increasing exponentially – YouTube, Facebook, LinkedIn, Twitter, weblogs, emails, Instagram, videos, audio,
  • High demand for Big data management and Analytics professionals
  • In the next few years, the analytics market will grow to 1/3rd of the global IT market from current 1/10th
  • Global and local businesses are implementing or planning to exploit big data
  • As per McKinsey report, by 2018, the United States alone could face a shortage of 190,000 people with deep analytical skills and 1.5 million managers / analysts with the knowledge to use the analysis of big data to make effective decisions.
  • Shortage of 2,50,000 trained data analysts in India
  • According to Institute of Analytics Professionals of Australia (IAPA), Big data analytics professionals draw higher median salary than other technologies
  • According to The Data Warehousing Institute (TDWI) survey, more than a third of the respondents are currently using some form of advanced analytics on Big Data, for Business Intelligence, Predictive Analytics and Data Mining tasks.
  • A survey by Deloitte shows that a large number of executives are using analytics that is helping their business needs.
  • Big Data Analytics is used everywhere – Healthcare, Consumer, Energy, Manufacturing, Technology, Banking, Insurance, Transport & Automotive, Aerospace, Defence, education, Smart Cities, Media & Entertainment, Telecom, Public Safety & Security

IDC FutureScape: Worldwise Big Data and Analytics 2016 Top 10 Predections

The 4 V’s of Big Data





Artificial Intelligence

What is Deep Learning

Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

Multiple nodes / computers connected to imitate human brains and which run machine learning algorithm autonomously to find the patterns, upgrade itself and find the trend.

Some uses of AI


  • Face recognition by Facebook using proprietary DeepFace technology
  • Virtual Personal assistants like Siri, Cortana
  • Google’s Driverless SmartCars
  • Purchase predictions by Flipkart, Amazon
  • News Stories’ recap by Yahoo!
  • Movie recommendation by Netflix
  • Skin disease diagnosis
  • Cancer detection
  • Human genome study
  • Diagnosis using X-ray image analysis
  • Sentiment analysis from social media posts

Industries and organizations where Big data, analytics and AI is being used



Analytics versions



Analytics 1.0: Deals with Data. Predictive Analytics is 5% while 95% is reporting

Analytics 2.0: Deals with Big Data. Predictive Analytics is 5% while 95% is reporting

Analytics 3.0: Deals with Big Data. Data is new economy. Predictive analytics is 90% while reporting is an automated commodity.


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