Big data gaurav

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Big Data Class 1

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<ul><li>1.BUMPER </li></ul><p>2. Understanding Big Data Class 1 Introduction to Big Data 3. Understanding Big Data Business Applications of Big Data Class 1 Introduction to Big Data 4. Understanding Big Data Business Applications of Big Data Technologies for handling Big Data Class 1 Introduction to Big Data 5. Understanding Big Data Business Applications of Big Data Technologies for handling Big Data Big Data Management Systems Databases &amp; Warehouses Class 1 Introduction to Big Data 6. Understanding Big Data Business Applications of Big Data Technologies for handling Big Data Big Data Management Systems Databases &amp; Warehouses Analytics &amp; Big Data Class 1 Introduction to Big Data 7. Topic 1 Class 1 Introduction to Big Data Understanding Big Data 8. What is Big Data? Topic 1 Understanding Big Data 9. What is Big Data? Topic 1 Understanding Big Data Structuring &amp; Elements 10. What is Big Data? Topic 1 Understanding Big Data Structuring &amp; Elements Application in Business &amp; Careers 11. DATA Personal Computers Facebook Twitter YouTube Google ATMs Drop Box Picasa 12. 2002 5 Exabytes Online Data 2009 281 Exabytes Online Data (56 Times Increase) 13. A pool of large-sized datasets to capture, store, What is Big Data? 14. A pool of large-sized datasets to capture, store, What is Big Data? search, share, transfer, analyse, and visualise 15. A pool of large-sized datasets to capture, store, What is Big Data? search, share, transfer, analyse, and visualise related information or data within an acceptable elapsed time. 16. Data = Information 17. Data = Information Information = Insight 18. Every second, consumers make 10,000 payment card transactions worldwide 19. Every second, consumers make 10,000 payment card transactions worldwide Every hour, Walmart handles more than 1 million customer transactions 20. Every second, consumers make 10,000 payment card transactions worldwide Every hour, Walmart handles more than 1 million customer transactions Everyday Twitters users post 500 million tweets per day 21. Every second, consumers make 10,000 payment card transactions worldwide Every hour, Walmart handles more than 1 million customer transactions Everyday Twitters users post 500 million tweets per day Facebook users post 2.7 billion likes and comments in a day 22. BIG DATA Is a new data challenge that requires leveraging existing systems differently 23. BIG DATA Is a new data challenge that requires leveraging existing systems differently Is classified in terms of: Volume (terabytes, records, transactions) Variety (internal, external, behavioural, or/and social) Velocity (near or real-time assimilation) 24. BIG DATA Is a new data challenge that requires leveraging existing systems differently Is classified in terms of: Volume (terabytes, records, transactions) Variety (internal, external, behavioural, or/and social) Velocity (near or real-time assimilation) Is usually unstructured and qualitative in Nature 25. Understanding target customer Advantages of Studying Big Data: 26. Understanding target customer Cutting down expenditures in the healthcare Advantages of Studying Big Data: 27. Understanding target customer Cutting down expenditures in the healthcare Increase in operating margins in retail Advantages of Studying Big Data: 28. Understanding target customer Cutting down expenditures in the healthcare Increase in operating margins in retail Profits with improvements in operational efficiency Advantages of Studying Big Data: 29. Sports Industries that Benefit: 30. Sports Science and Research Industries that Benefit: 31. Sports Science and Research Security and Law Enforcement Industries that Benefit: 32. Sports Science and Research Security and Law Enforcement Financial Trading Industries that Benefit: 33. Procurement Departments that can Benefit: 34. Procurement Product Development Departments that can Benefit: 35. Procurement Product Development Manufacturing Departments that can Benefit: 36. Procurement Product Development Manufacturing Distribution Departments that can Benefit: 37. Procurement Product Development Manufacturing Distribution Marketing Departments that can Benefit: 38. Procurement Product Development Manufacturing Distribution Marketing Price Management Departments that can Benefit: 39. Procurement Product Development Manufacturing Distribution Marketing Price Management Merchandising Departments that can Benefit: 40. Procurement Product Development Manufacturing Distribution Marketing Price Management Merchandising Sales Departments that can Benefit: 41. Procurement Product Development Manufacturing Distribution Marketing Price Management Merchandising Sales Store operations Departments that can Benefit: 42. Procurement Product Development Manufacturing Distribution Marketing Price Management Merchandising Sales Store operations Human Resources Departments that can Benefit: 43. Flu Indications &amp; WarningsMassive Data Collection Analyse Collected Data Early Warnings for Flu Plague 44. Social Data from Networking Sites reveals Behavioural Patterns 45. Use Big Data for Growth &amp; Value Addition 46. RECAP What is Big Data, its advantages and various sources 47. BUMPER 48. BUMPER 49. Topic 1 Class 1 - Introduction to Big Data Understanding Big Data 50. What is Big Data? Class 1 - Introduction to Big Data 51. What is Big Data? Class 1 - Introduction to Big Data Structuring &amp; Elements 52. What is Big Data? Class 1 - Introduction to Big Data Structuring &amp; Elements Application in Business &amp; Careers 53. How do I choose a book, of the millions available on my favorite sites or stores? How can I use the vast amount of data and information I come across? 54. How do I keep myself updated of events, news? Which news articles should I read? How do I choose a book, of the millions available on my favorite sites or stores? How can I use the vast amount of data and information I come across? 55. Formats of Data: 56. Formats of Data: 57. Formats of Data: 58. Formats of Data: 59. Internal Organisational or enterprise data Sources of Data: External - Social Data from the internet or Government 60. Structured Data Unstructured Data Semi- Structured Data BIG DATA 61. Structured Data 62. Has a predefined format Features of Structured Data: 63. Has a predefined format Resides in fixed fields within a record Features of Structured Data: 64. Has a predefined format Resides in fixed fields within a record Has their attributes mapped Features of Structured Data: 65. Has a predefined format Resides in fixed fields within a record Has their attributes mapped Used to report against predetermined data types Features of Structured Data: 66. Sources of Structured Data: Relational databases 67. Sources of Structured Data: Relational databases Flat files in record format 68. Sources of Structured Data: Relational databases Flat files in record format Multidimensional databases 69. Sources of Structured Data: Relational databases Flat files in record format Multidimensional databases Legacy databases 70. Unstructured Data 71. Sources of Unstructured Data: Organisational Data 72. Sources of Unstructured Data: Organisational Data Social Media 73. Sources of Unstructured Data: Organisational Data Social Media Mobile Data 74. Challenges of Using Unstructured Data: Difficulty and time consumption in making sense 75. Challenges of Using Unstructured Data: Difficulty and time consumption in making sense Difficulty in combining and linking unstructured data to more structured information 76. Challenges of Using Unstructured Data: Difficulty and time consumption in making sense Difficulty in combining and linking unstructured data to more structured information Cost-addition in terms of the storage wastage and human resource needed 77. Semi-Structured Data 78. Sources of Semi-Structured data: Database systems 79. Sources of Semi-Structured data: Database systems File systems like Web data and bibliographic data 80. Sources of Semi-Structured data: Database systems File systems like Web data and bibliographic data Data exchange formats like scientific data 81. Sl. No Name E-mail 1. Sam Jacobs smj@xyz.com 2. First Name David davidb@xyz.com Last Name Brown 82. Volume 83. Velocity 84. Variety 85. What is Big Data? Class 1 - Introduction to Big Data Structuring &amp; Elements Application in Business &amp; Careers 86. Big Data Application In Business Analytics 87. What are the areas where Big Data can be applied? 88. Transportation Provides improved traffic information and autonomous features 89. Education Through innovative approaches for teachers to analyze students 90. Travel Apply analytics to pricing, inventory, and advertising to improve customer experiences 91. Governments To make informed decisions for fraud management, discover unknown threats, ensure security of global supply chain 92. Healthcare To ensure clinical protocols that will ensure the best health outcome for patients 93. Careers in Big Data 94. BIG Career Opportunities 95. Major Big Data Hiring Companies: Product companies, e.g., Oracle Technology drivers, e.g., Google Services companies, e.g., EMC Data analytics companies, e.g., Splunk 96. The most common job titles in Big Data include: Big Data Analyst 97. The most common job titles in Big Data include: Big Data Analyst Big Data Scientist 98. The most common job titles in Big Data include: Big Data Analyst Big Data Scientist Big Data Developer 99. Module 1 Introduction to Big Data 100. Module 1 Introduction to Big Data Big Data Analyst Certification Track Big Data Developer Certification Track 101. Module 1 Introduction to Big Data Big Data Analyst Certification Track Big Data Developer Certification Track Module 2 Introduction to Analytics &amp; R Programming Module 3 Data Analysis Using R Module 4 Advanced Analytics Using R Module 2 Managing a Big Data Ecosystem 102. Module 1 Introduction to Big Data Big Data Analyst Certification Track Big Data Developer Certification Track Module 2 Introduction to Analytics &amp; R Programming Module 3 Data Analysis Using R Module 4 Advanced Analytics Using R Module 2 Managing a Big Data Ecosystem Module 5 Machine Learning Concepts Module 3 Storing &amp; Processing Data: HDFS &amp; MapReduce Module 4: Increasing Efficiency with Hadoop Tools Module 5 Additional Hadoop Tools: ZooKeeper, Sqoop, Flume, YARN &amp; Storm 103. Module 1 Introduction to Big Data Big Data Analyst Certification Track Big Data Developer Certification Track Module 2 Introduction to Analytics &amp; R Programming Module 3 Data Analysis Using R Module 4 Advanced Analytics Using R Module 2 Managing a Big Data Ecosystem Module 5 Machine Learning Concepts Module 3 Storing &amp; Processing Data: HDFS &amp; MapReduce Module 4: Increasing Efficiency with Hadoop Tools Module 5 Additional Hadoop Tools: ZooKeeper, Sqoop, Flume, YARN &amp; Storm Module 6 Social Media, Mobile Analytics &amp; Visualisation Module 7 Industry Applications of Big Data Applications Module 6 Leveraging NoSQL &amp; Hadoop: Real Time, Security &amp; Cloud Module 7 Commercial Hadoop Distribution &amp; Management Tools 104. Module 1 Introduction to Big Data Big Data Analyst Certification Track Big Data Developer Certification Track Module 2 Introduction to Analytics &amp; R Programming Module 3 Data Analysis Using R Module 4 Advanced Analytics Using R Module 2 Managing a Big Data Ecosystem Module 5 Machine Learning Concepts Module 3 Storing &amp; Processing Data: HDFS &amp; MapReduce Module 4: Increasing Efficiency with Hadoop Tools Module 5 Additional Hadoop Tools: ZooKeeper, Sqoop, Flume, YARN &amp; Storm Module 6 Social Media, Mobile Analytics &amp; Visualisation Module 7 Industry Applications of Big Data Applications Module 6 Leveraging NoSQL &amp; Hadoop: Real Time, Security &amp; Cloud Module 7 Commercial Hadoop Distribution &amp; Management Tools Complete Project Wrox Certified Big Data Analyst/ Developer 105. Technical Skills Required for a Big Data Analyst: 106. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce 107. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive 108. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive SQL and NoSQL languages such as Impala, Hive and Pig 109. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive SQL and NoSQL languages such as Impala, Hive and Pig Analytical tools such as SAS, R, Tableau 110. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive SQL and NoSQL languages such as Impala, Hive and Pig Analytical tools such as SAS, R, Tableau Statistical techniques to implement text analytics solutions 111. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive SQL and NoSQL languages such as Impala, Hive and Pig Analytical tools such as SAS, R, Tableau Statistical techniques to implement text analytics solutions Data handling and manipulation techniques 112. Technical Skills Required for a Big Data Analyst: Handle &amp; analyse massive data sets using MapReduce Hadoop &amp; components Hbase &amp; Hive SQL and NoSQL languages such as Impala, Hive and Pig Analytical tools such as SAS, R, Tableau Statistical techniques to implement text analytics solutions Data handling and manipulation techniques Generate client ready dashboards, reports and visualizations 113. Soft Skills Required: Strong written &amp; verbal communication skills 114. Soft Skills Required: Strong written &amp; verbal communication skills Analytical Ability 115. Soft Skills Required: Strong written &amp; verbal communication skills Analytical Ability Basic understanding of how a business works 116. Future of Big Data 117. RECAP What are the various types and structures of Big Data and the elements that form it What are the business applications of Big Data and the career opportunities associated 118. BUMPER 119. BUMPER 120. BIG DATA 121. Topic 2 Business Applications of Big Data Class 1: Introduction to Big Data 122. Social Media 123. Topic 2 Business Applications of Big Data Significance of Social Network Data 124. Topic 2 Business Applications of Big Data Significance of Social Network Data Financial Fraud &amp; Big Data 125. Topic 2 Business Applications of Big Data Significance of Social Network Data Financial Fraud &amp; Big Data Fraud Detection in Insurance 126. Topic 2 Business Applications of Big Data Significance of Social Network Data Financial Fraud &amp; Big Data Fraud Detection in Insurance Use in Retail Industry 127. Significance of Social Network Data What is Socia...</p>