《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（PPT课件，第3版）Chapter 06 Big Data and Analytics

Business Intelligence: A Managerial Perspective on Analytics(3rd Edition) INTELLIGENCE A Managerial Perspective on Analytics Chapter 6: Big Data and Analytics EFRAUTI RRAN

Chapter 6: Big Data and Analytics Business Intelligence: A Managerial Perspective on Analytics (3rd Edition)

Learning Objectives Learn what Big Data is and how it is changing the world of analytics Understand the motivation for and business drivers of Big Data analytics Become familiar with the wide range of enabling technologies for Big Data analytics Learn about Hadoop, MapReduce, and NosQL as they relate to Big data analytics Understand the role of and capabilities/skills for data scientist as a new analytics profession Continued.) Copynight@ 2014 Pearson Education, Inc Slide 6-2

Copyright © 2014 Pearson Education, Inc. Slide 6 - 2 Learning Objectives ▪ Learn what Big Data is and how it is changing the world of analytics ▪ Understand the motivation for and business drivers of Big Data analytics ▪ Become familiar with the wide range of enabling technologies for Big Data analytics ▪ Learn about Hadoop, MapReduce, and NoSQL as they relate to Big Data analytics ▪ Understand the role of and capabilities/skills for data scientist as a new analytics profession (Continued…)

Learning Objectives Compare and contrast the complementary uses of data warehousing and Big Data Become familiar with the vendors of Big data tools and services Understand the need for and appreciate the capabilities of stream analytics Learn about the applications of stream analytics Copynight@ 2014 Pearson Education, Inc Slide 6-3

Copyright © 2014 Pearson Education, Inc. Slide 6 - 3 Learning Objectives ▪ Compare and contrast the complementary uses of data warehousing and Big Data ▪ Become familiar with the vendors of Big Data tools and services ▪ Understand the need for and appreciate the capabilities of stream analytics ▪ Learn about the applications of stream analytics

Opening Vignette Big Data Meets Big Science at CERN Situation Problem Solution Results Answer discuss the case questions Copynight@ 2014 Pearson Education, Inc Slide 6-4

Copyright © 2014 Pearson Education, Inc. Slide 6 - 4 Opening Vignette… Big Data Meets Big Science at CERN ▪ Situation ▪ Problem ▪ Solution ▪ Results ▪ Answer & discuss the case questions

Questions for the Opening Vignette What iS CERN, and why is it important to the world of science? How does the Large Hadron Collider work? What does it produce? What is the essence of the data challenge at CERN? How significant is it? What was the solution? How were the Big data challenges addressed with this solution? What were the results? Do you think the current solution is sufficient? Copynight@ 2014 Pearson Education, Inc Slide 6-5

Copyright © 2014 Pearson Education, Inc. Slide 6 - 5 Questions for the Opening Vignette ▪ What is CERN, and why is it important to the world of science? ▪ How does the Large Hadron Collider work? What does it produce? ▪ What is the essence of the data challenge at CERN? How significant is it? ▪ What was the solution? How were the Big Data challenges addressed with this solution? ▪ What were the results? Do you think the current solution is sufficient?

Big Data-Definition and Concepts Big Data means different things to people with different backgrounds and interests Traditionally, Big Data"= massive volumes of data E.g., volume of data at CERN, NASA, Google Where does the Big Data come from? Everywhere! Web logs, RFID, GPS systems, sensor networks, social networks. Internet-based text documents Internet search indexes, detail call records, astronomy, atmospheric science, biology, genomics, nuclear physics, biochemical experiments, medical records, scientific research, military surveillance, multimedia archives, Copynight@ 2014 Pearson Education, Inc Slide 6-6

Copyright © 2014 Pearson Education, Inc. Slide 6 - 6 Big Data - Definition and Concepts ▪ Big Data means different things to people with different backgrounds and interests ▪ Traditionally, “Big Data” = massive volumes of data ▪ E.g., volume of data at CERN, NASA, Google, … ▪ Where does the Big Data come from? ▪ Everywhere! Web logs, RFID, GPS systems, sensor networks, social networks, Internet-based text documents, Internet search indexes, detail call records, astronomy, atmospheric science, biology, genomics, nuclear physics, biochemical experiments, medical records, scientific research, military surveillance, multimedia archives, …

Technology Insights 6.1 The Data Size Is Getting Big, Bigger, Hadron Collider -1 PB/sec Boeing jet -20 TB/hr Facebook -500 TB/day You lube -1 TB/4 min Name Symbo Value Kilobyte The proposed Square Kilometer Array telescope gigabyte (the world's proposed terabyte Petabyte biggest telescope)-1 EB/day Zettabyte Yottaby Brontobyte BB GeB 30 "Not an official SI (International System of Units) name/symbol, yet Copynight@ 2014 Pearson Education, Inc Slide 6-7

Copyright © 2014 Pearson Education, Inc. Slide 6 - 7 Technology Insights 6.1 The Data Size Is Getting Big, Bigger, … ▪ Hadron Collider - 1 PB/sec ▪ Boeing jet - 20 TB/hr ▪ Facebook - 500 TB/day ▪ YouTube – 1 TB/4 min ▪ The proposed Square Kilometer Array telescope (the world’s proposed biggest telescope) – 1 EB/day

Big Data-Definition and Concepts Big data is a misnomer Big Data is more than just big The Vs that define Big Data Volume Variety Velocity Veraci Variability Value Copynight@ 2014 Pearson Education, Inc Slide 6-8

Copyright © 2014 Pearson Education, Inc. Slide 6 - 8 Big Data - Definition and Concepts ▪ Big Data is a misnomer! ▪ Big Data is more than just “big” ▪ The Vs that define Big Data ▪ Volume ▪ Variety ▪ Velocity ▪ Veracity ▪ Variability ▪ Value ▪ …

Big Data-Definition and Concepts Big Data is not new! Traditionally, Big Data= massive volumes of data Volume of data at CERN, NASA, Google Where does the Big Data come from? Everywhere! Web logs, RFID, GPS systems, sensor networks, social networks, Internet-based text documents Internet search indexes, detail call records, astronomy, atmospheric science, biology, genomics, nuclear physics biochemical experiments, medical records, scientific research, military surveillance, multimedia archives Copynight@ 2014 Pearson Education, Inc Slide 6-9

Copyright © 2014 Pearson Education, Inc. Slide 6 - 9 Big Data - Definition and Concepts ▪ Big Data is not new! ▪ Traditionally, “Big Data” = massive volumes of data ▪ Volume of data at CERN, NASA, Google, … ▪ Where does the Big Data come from? ▪ Everywhere! Web logs, RFID, GPS systems, sensor networks, social networks, Internet-based text documents, Internet search indexes, detail call records, astronomy, atmospheric science, biology, genomics, nuclear physics, biochemical experiments, medical records, scientific research, military surveillance, multimedia archives, …

A High-Level Conceptual Architecture for Big Data Solutions(by AsterData/Teradata) UNIFIED DATA ARCHITECTURE System Conceptual View MOVE MANAGE ACCESS DATA PLATFORM INTEGRATED DATA WAREHOUSE Customers Images Frontline Workers 司 Machine DISCOVERY PLATFORM Analysts EVENT PROCESSING DATA USERS Copynight@ 2014 Pearson Education, Inc Slide 6-10

Copyright © 2014 Pearson Education, Inc. Slide 6 - 10 A High-Level Conceptual Architecture for Big Data Solutions (by AsterData / Teradata) Math and Stats Data Mining Business Intelligence Applications Languages Marketing ANALYTIC TOOLS & APPS USERS DISCOVERY PLATFORM INTEGRATED DATA WAREHOUSE DATA PLATFORM MOVE MANAGE ACCESS UNIFIED DATA ARCHITECTURE System Conceptual View Marketing Executives Operational Systems Frontline Workers Customers Partners Engineers Data Scientists Business Analysts EVENT PROCESSING ERP SCM CRM Images Audio and Video Machine Logs Text Web and Social BIG DATA SOURCES ERP