Tools and techniques adopted for big data analytics
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This document discusses tools and techniques for big data analytics. It begins by defining big data and explaining why big data analysis is important for businesses. It then outlines the characteristics and history of big data, as well as the challenges and phases of big data analysis. The document proceeds to describe several tools and techniques used for big data analytics, including machine learning, natural language processing, and visualization. It provides examples of how these tools and techniques have been applied through case studies of Indian elections, AirBnB, and Shoppers Stop.
Tools and techniques adopted for big data analytics
- 2. Tools and techniques adopted for Big Data Analytics JOSEPH FRANCIS 1BI11IM020
- 3. WHAT IS BIG DATA? WHY ANALYSIS ON BIG DATA IS CRUCIAL FOR VALUE BASED SERVICES AND PRODUCTS ? BIG DATA CHARACTERISTICS A BRIEF HISTORY ON ORIGINS OF BIG DATA PHASES IN BIG DATA ANALYSIS CHALLENGES IN BIG DATA ANALYSIS TOOLS AND TECHNIQUES FOR DATA ANALYTICS CASE STUDIES CONCLUSION
- 5. WHAT IS BIG DATA? Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
- 6. WHY ANALYSIS ON BIG DATA IS CRUCIAL FOR VALUE BASED SERVICES AND PRODUCTS ? BUSINESS INTELLIGENCE DECISION SUPPORT PREDICTIVE ANALYTICS GOVERNMENTS HEALTHCARE RESEARCH MARKETTING STRATEGIES
- 13. A brief history on origins of big data 1880 - The Start of Information Overload 8years to complete US census 1932 - The Population Boom 1956 - Virtual Memory 1966 - Centralized Computing Systems Enter the Scene 1970 - Relational Database 1985 - Manufacturing Resources Planning Systems 1989 - Business Intelligence 1995 - The World Wide Web Explodes 1999 - Predictive Analysis Changes Business as Usual http://www.winshuttle.com/big-data-timeline/
- 14. Data Acquisition and Recording Information Extraction and Cleaning Data Integration, Aggregation, and Representation Query Processing, Data Modelling, and Analysis Interpretation Phases in Big Data analysis
- 15. CHALLENGES IN DATA ANALYSIS HETEROGINITY TIMELINESS SCALE PRIVACY HUMAN COLLABORATION
- 17. Tools and Techniques a/b testing Crowdsourcing Genetic algorithms Machine learning Natural language processing Time series analysis Visualization Data mining Association rule learning Classification tree analysis Regression analysis
- 18. a/b testing It is a form of statistical hypothesis testing with two variants leading to the technical term, Two-sample hypothesis testing, used in the field of statistics. a = H0: NULL HYPOTHESIS b = H1:ALTERNATE HYPOTHESIS
- 20. Crowdsourcing Crowdsourcing represents the act of a company or institution taking a function once performed by employees and outsourcing it to an undefined (and generally large) network of people in the form of an open call. Analysis of the reviews for opinion Analysis of the interactions for need and intent Analysis of social network interactions
- 22. Machine learning - scientific discipline that explores the construction and study of algorithms. - by building a model from example inputs and using that to make predictions or decisions. - by dynamic instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline which also specializes in prediction-making.
- 24. Indian Elections 2014 - size of the Indian electorate. With 814 million voters, in comparison to the USA’s 193.6 million and the UK’s 45.5 million. 0 100 200 300 400 500 600 700 800 900 INDIA USA UK - variety of data – India’s voter rolls in 12 different languages and 900,000 PDF’s amounting to 25 million pages made for a heterogeneous, non- uniform and deeply diverse information set. - the veracity of the information was often questionable one report noted that some voters were listed as 19,545 years old, and others a confounding 0 years old. Name overlapping (there are 327,000 women named “Sita” in Bihar alone) only further complicated the process.
- 25. A tactical scenario BJP WEBSITE BIKE WEBSITE JOB PORTAL INDIA DESERVES BETTER
- 26. Air BnB
- 27. -Airbnb’s team had a hunch that better photos would increase rentals. -They tested the idea by putting the least effort possible into a test that would give them valid results. -When the experiment showed good results, they built the necessary components and rolled it out to all customers.
- 29. Shoppers stop Shoppers Stop stores retails clothing, accessories, handbags, shoes, jewelry, fragrances, cosmetics, health and beauty products, home furnishing and decor products. Shoppers Stop launched its e-store with delivery across major cities in India in 2008. The website retails all the products available at Shoppers Stop stores, including apparel, cosmetics and accessories. Shoppers Stop opened stores in Amritsar, Bhopal and Aurangabad.
- 30. After analysing its First Citizen base, the company had observed that not all those who buy shirts also buy trousers. But those who buy both men’s shirts and trousers spend 60% more a year on average than those who buy only shirts, and thrice as much as those who don’t buy men’s shirts at all 9,00,000
- 31. - included customers who showed a pattern of being interested in new brands in other non trouser categories. They were sent information on new trouser brand launches and fits. - exhibited multiple buying patterns in other categories. They were sent attractive deals if they bought two or more trousers. - “control group” to measure success or failure of the promotions. The campaign proved 30 % increase in sales equivalent to 30 crore