The first part is an overview of big data governance from Chapter 1 Chapter 2 Big data governance framework 2. 1 Big data type 2.2 Information governance standards 2.3 Industry and function scenarios of big data governance Chapter 3 Maturity assessment 3. 1 IBM Information Governance Committee's Maturity Model 3.2 Examples of Assessing Maturity Chapter 4 Business Case 4.6543 8+0 Improving Real-time Operation and Passenger Safety through Big Data Governance 4.2 Quantifying the Financial Impact of Big Data Governance on Customer Privacy 4.3 Managing the Life Cycle of Big Data, Reduce IT costs 4.4 Assess the impact of data quality and master data on big data plans 4.5 Calculate the value of big data quality Chapter 5 Roadmap 5. 1 Roadmap Case Study Part II Guide to Big Data Governance Chapter 6 Organization of Big Data Governance 6. 1 Draw the key flow chart and establish the responsibility allocation model. Identify stakeholders in big data governance 6.2 Identify the appropriate combination of new roles and existing roles 6.3 Appoint big data directors as appropriate 6.4 Add big data responsibilities as appropriate based on traditional information governance roles. 6.5 Establish a mixed information governance organization including big data. Chapter 7 Metadata 7. 1 Create a thesaurus reflecting the business definitions of key big data terms. 7.2 Understand the continuous support of metadata in ApacheHadoop. 7.3 Mark sensitive big data in the business thesaurus. 7.4 Import technical metadata from related big data storage. 7 .5 Linking related data sources with terms in the business terminology thesaurus 7.6 Monitoring the flow of big data with operational metadata 7.7 Retaining technical metadata to support data pedigree and impact analysis 7.8 Collecting metadata from unstructured files and supporting enterprise search 7.9 Expanding existing metadata roles, Including Chapter 8 Big Data in Big Data Privacy 8. 1 Identifying Sensitive Big Data 8.2 Marking Sensitive Big Data in Metadatabase 8.3 Handling Privacy Legislation and Privacy Restrictions at National and State (Province) Levels 8.4 Managing Cross-border Flow of Personal Data 8.5 Monitoring Privileged Users' Access to Sensitive Big Data Chapter 9 Big Data Quality 9. 1 Collaborate with business stakeholders to establish and measure the confidence interval of big data quality. 9.2 Use quasi-structured and unstructured data to improve the quality of structured data with sparse population. 9.3 Use streaming data analysis technology to solve data quality problems in memory, without inputting intermediate results into hard disk. 9.4 Appoint a data supervisor to take charge of the information governance committee. It is responsible for improving the measurement quality. Chapter 65438 +00 Business Process Integration 10. 1 Identify key processes that will be affected by big data governance 10.2 Establish a flowchart of key activities 10.3 For key steps in business processes, Formulate the big data governance policy Chapter 65438 +0 1 master data integration1.1Improve the quality of master data to support the big review of social media platform policies to support the big data governance plan1.4 Determine the degree of integration with master data management/kloc. .5 Mining useful information from unstructured texts to enrich the life cycle of master data Chapter 12 Managing big data 12. 1 Expanding retention according to regulations and business requirements. Incorporate big data into IT 12.2 to provide legal reserved areas and support electronic discovery) 12.3 compress big data and archive IT, reduce IT costs and improve application performance 12.4 manage the life cycle of real-time streaming data 12.5 retain social media records to meet regulatory requirements and support electronic evidence display based on regulatory and business requirements. Part III Types of Big Data Chapter 13 Web and Social Media Data 13. 1 When formulating policies on the acceptable use of customer social media data, Considering the ever-changing laws and customs 13.2 Formulate policies on the acceptable use of social media data by employees and job seekers 13.3 Evaluate the quality of social media data with confidence intervals 13.4 Formulate policies on the acceptable use of Cookies and other network tracking devices on the basis of not infringing privacy and complying with regulatory requirements 13.5, Define the strategy of connecting online and offline data 13.6 Ensure the consistency of network statistics Chapter 14 Machine-to-Machine Data 14. 1 Evaluate the currently available geographic location data 14.2 Formulate the strategy for the acceptable use of customer geographic location data 14.3 Formulate employees. Use policy 14.4 to ensure the privacy of RFID data 14.5 to formulate policies related to the privacy of other types of M2M data 14.6 to deal with the quality problems of metadata and M2M data 14.7 to formulate policies related to the retention period of M2M data 14.8 to improve the quality of master data, Support the M2M plan 14.9 to ensure that SCADA facilities are not affected by the ever-developing regulations on the use of biometric data of customers and employees. Chapter 17 Manually generated data 17. 1 formulate policies to shield sensitive manually generated data 17.2 Use unstructured manually generated data to improve the quality of structured data/. Reduce costs and follow the regulatory requirements 17.4 to gain insight from unstructured artificially generated data to enrich the fourth part of MDM. Chapter 18 Health care institutions 18. 1 Use unstructured data to improve the quality of structured data with sparse population 18.2 Extract more unavailable clinical factors from structured data 18.3 Set consistent definitions of key business terms 18.4 Ensure cross-departments. Meet the privacy requirements of protected health information 18.6 creative management reference data, in order to gain more clinical insight, Chapter 19 Public Utilities Department 19. 1 meter reading 19.2 integrity of reference key words 19.3 abnormal meter reading 19.4 data quality of customer address 19.5 information lifecycle management/klc. 9.7 Technical Architecture Chapter 20 Communication Service Providers 20. 1 Big Data Type 20.2 Big Data and Master Data Integration 20.3 Big Data Privacy 20.4 Big Data Quality 20.5 Big Data Lifecycle Management Part V Big Data Technology Part 2 1 Big Data Reference Architecture 2 1 .2 Open Source Infrastructure Component 2/kloc. .3 Hadoop distributes metadata of 26555438+00 big data 2 1. 1 information policy management 2 1. 12 master data management 2 1. 13 data warehouse and data mart 21 Private 2 1. 16 Big Data Lifecycle Management 2 1. 17 Cloud Chapter 22 Big Data Platform 22. 1 IBM 22.2 Oracle Bone Inscriptions 22.3 SAP 22.4 Microsoft 22.5 HP 22.6 Informatica 22.7 SAS 22.8 Teradata 2.2.9 EMC 22.10 Amazon 22.1google22.12 Pentaho22./kloc-0.