Business Resilience System (BRS) : Real and near Real Time Analysis and Decision Making System.

By: Zohuri, BahmanContributor(s): Moghaddam, MasoudMaterial type: TextTextSeries: eBooks on DemandPublisher: Cham : Springer, 2017Copyright date: ©2017Description: 1 online resource (436 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9783319534176Subject(s): Politics and warGenre/Form: Electronic books.Additional physical formats: Print version:: Business Resilience System (BRS): Driven Through Boolean, Fuzzy Logics and Cloud ComputationDDC classification: 658.47 LOC classification: TA1-2040Online resources: Click here to view this ebook.
Contents:
Intro -- Dedication -- Preface -- Acknowledgments -- Contents -- About the Authors -- Chapter 1: Resilience and Resilience System -- 1.1 Introduction -- 1.2 Resilience and Stability -- 1.3 Reactive to Proactive Safety Through Resilience -- 1.4 The Business Resilience System Backdrop -- 1.5 Risk Atom Key Concept -- 1.6 Business Resilience System Features -- 1.7 Business Resilience System Project Plan -- 1.8 Summary of Business Resilience System -- References -- Chapter 2: Building Intelligent Models from Data Mining -- 2.1 Introduction -- 2.2 Risk Assessment and Risk Element -- 2.2.1 How the Risk Is Determined -- 2.2.2 Acceptable Risk Increase -- 2.2.3 Acceptable Risk in Auditing -- 2.2.4 Risk Analysis Process -- 2.3 Incident Response -- 2.3.1 What Is Incident Response -- 2.3.2 Real-Life Incidents -- 2.3.3 Incident Response Planning Program -- 2.3.3.1 Establishing the Incident Response Program -- 2.3.4 Tools of the Trade -- 2.3.5 What Is Out There -- 2.3.6 Risk Assessment and Incident Response -- 2.4 Predictive Modeling -- 2.4.1 Prediction in Enterprise Management -- 2.4.2 The Benefits and Predictive Modeling Basics -- 2.4.3 Basic Infrastructure of Modeling -- 2.4.4 Models and Event State Categorization -- 2.4.5 Model Type and Outcome Categorization -- 2.4.6 Critical Feature Selection for Predictive Models -- 2.4.7 Core Features of Robust Predictive Models -- 2.4.8 Model Type Selection -- 2.4.9 Basic Principles of Predictive Models -- References -- Chapter 3: Event Management and Best Practice -- 3.1 Introduction to Event Management -- 3.2 Event Management Terminology -- 3.2.1 Event -- 3.2.2 Event Management -- 3.2.3 Event Processing -- 3.2.4 Automation and Automated Actions -- 3.3 Concepts and Issues -- 3.3.1 Event Flow -- 3.3.2 Filtering and Forwarding -- 3.3.3 Duplicate Detection and Throttling -- 3.3.4 Correlation.
3.3.5 Event Synchronization -- 3.3.6 Notification -- 3.3.7 Trouble Ticketing -- 3.3.8 Escalation -- 3.3.9 Maintenance Mode -- 3.3.10 Automation -- 3.4 Planning Considerations -- 3.4.1 IT Environment Assessment -- 3.4.2 Organizational Considerations -- 3.4.3 Policies -- 3.4.4 Standards -- Reference -- Chapter 4: Event Management Categories and Best Practices -- 4.1 Introduction -- 4.2 Implementation Approaches -- 4.2.1 Send All Possible Events -- 4.2.2 Start with Out-of-the-Box Notifications and Analyze Reiteratively -- 4.2.3 Report Only Known Problems and Add Them to the List as They Are Identified -- 4.2.4 Choose Top X Problems from Each Support Area -- 4.2.5 Perform Event Management and Monitoring Design -- 4.3 Policies and Standards -- 4.3.1 Reviewing the Event Management Process -- 4.3.2 Defining Severities -- 4.3.3 Implementing Consistent Standards -- 4.3.4 Assigning Responsibilities -- 4.3.5 Enforcing Policies -- 4.4 Filtering -- 4.4.1 Why Filter -- 4.4.2 How to Filter -- 4.4.3 Where to Filter -- 4.4.4 What to Filter -- 4.4.5 Filtering Best Practices -- 4.5 Duplicate Detection and Suppression -- 4.5.1 Suppressing Duplicate Events -- 4.5.2 Implications of Duplicate Detection and Suppression -- 4.5.3 Duplicate Detection and Throttling Best Practices -- 4.6 Correlation -- 4.6.1 Correlation Best Practice -- 4.6.2 Implementation Considerations -- 4.7 Notification -- 4.7.1 How to Notify -- 4.7.2 Notification Best Practices -- 4.8 Escalation -- 4.8.1 Escalation Best Practices -- 4.8.2 Implementation Considerations -- 4.9 Event Synchronization -- 4.9.1 Event Synchronization Best Practices -- 4.10 Trouble Ticketing -- 4.10.1 Trouble Ticketing -- 4.11 Maintenance Mode -- 4.11.1 Maintenance Status Notification -- 4.11.2 Handling Events from a System in Maintenance Mode -- 4.11.3 Prolonged Maintenance Mode -- 4.11.4 Network Topology Considerations.
4.12 Automation -- 4.12.1 Automation Best Practice -- 4.12.2 Automation Implementation Considerations -- 4.13 Best Practices Flowchart -- Reference -- Chapter 5: Dynamic and Static Content Publication Workflow -- 5.1 Introduction -- 5.2 Business Workflow -- 5.2.1 Workflow Management -- 5.2.2 Business Rules Engine -- 5.2.3 Business Rules Platform -- 5.2.4 Business Transformation -- 5.3 Dynamic Publishing and Processes -- 5.4 E-commerce World and Dynamic Content Publication Workflow -- 5.5 Overall Concepts/Philosophy -- 5.6 Business Resilience System Technology Topology Design -- 5.6.1 Terms and Definitions -- 5.6.2 Architecture Diagram and Logical Architecture -- 5.6.3 Publication Process and Actors and Workflow -- 5.6.4 Static Content Publication Workflow -- 5.6.5 Product Image Data Storage -- 5.6.6 Product Image Data Publishing and Editing -- 5.6.7 Transaction Data Management Process -- 5.6.8 Hardware/Software Specifications -- 5.6.9 Webmail and Discussion Board Interface -- 5.6.10 Member Address Book -- 5.6.11 Site and Database Search -- 5.6.12 Load Balancing and Web Farm Management -- 5.7 System Interfaces -- 5.8 Technical Approach -- 5.8.1 Technical Requirements for Phase I -- 5.8.2 Technical Requirements Beyond Scope for Phase I -- 5.8.3 Proposed Hardware and Network Architecture (Fig. 5.9) -- 5.8.4 Logical Architecture for Live Environment -- 5.8.5 Technical Risks -- 5.8.5.1 Phase I Items Not Estimated -- 5.8.5.2 Recommended Solution -- 5.8.5.3 User Home Pages -- References -- Chapter 6: What Is Boolean Logic and How It Works -- 6.1 Introduction -- 6.2 How Bits and Bytes Work -- 6.2.1 The Base-2 System and the 8-Bit Byte -- 6.2.2 The Standard ASCII Character Set -- 6.2.3 Byte Prefixes and Binary Math -- 6.3 Logical Gates -- 6.4 Simple Adders -- 6.5 Full Adders -- 6.6 Truth Tables -- 6.6.1 Practical Truth Tables -- 6.7 Summary -- Reference.
Chapter 7: What Is Fuzzy Logic and How It Works -- 7.1 Introduction -- 7.2 What Is Fuzzy Logic -- 7.3 Fuzzy Logic and Fuzzy Sets -- 7.4 The Fuzzy Logic Method -- 7.4.1 Fuzzy Perception -- 7.4.2 Novices Can Beat the Pros -- 7.4.3 A Milestone Passed for Intelligent Life on Earth -- 7.4.4 Fuzzy Logic Terms Found in Books and Articles -- 7.5 The World's First Fuzzy Logic Controller -- 7.5.1 Progress in Fuzzy Logic -- 7.5.2 Fuzzy Logic Control Input: Human and Computer -- 7.5.3 More About How Fuzzy Logic Works -- 7.6 Rationale for Fuzzy Logic -- Reference -- Chapter 8: Mathematics and Logic Behind Boolean and Fuzzy Computation -- 8.1 Mathematics of Boolean Logic and Algebra -- 8.1.1 Definition and Simple Properties -- 8.1.2 Special Classes of Boolean Algebras -- 8.1.3 Structure Theory and Cardinal Functions on Boolean Algebras -- 8.1.4 Decidability and Undecidability Questions -- 8.1.5 Lindenbaum-Tarski Algebras -- 8.1.6 Boolean-Valued Models -- 8.2 Mathematics of Fuzzy Logic -- 8.2.1 More Description of Mathematics of Fuzzy -- References -- Chapter 9: Building Intelligent Models from Data Mining and Expert Knowledge -- 9.1 Introduction -- 9.2 Introduction to Predictive Modeling -- 9.2.1 Simple Linear Regression -- 9.3 Knowledge-Based Models -- 9.4 Knowledge, Intelligence, and Models -- 9.5 Model Development and Protocycling -- 9.6 Subject Matter Experts and Acquired Knowledge -- 9.7 The Methodology -- 9.8 Fuzzy Knowledge Bases for Business Process Modeling -- 9.9 Risk Assessment Model -- 9.9.1 Setting High Goals and Exceeding Them -- 9.9.2 Defining the Problem -- 9.9.3 Moving Beyond Log Management and Security Software -- 9.9.4 Expanding the Approach with Sense Analytics -- 9.10 Risk and Vulnerability Management -- 9.10.1 Threat Detection -- 9.10.2 Forensics Investigation -- 9.10.3 Incident Response -- 9.10.4 Regulatory Compliance.
9.11 Keeping Up with Evolving Threats and Risks -- 9.12 Conclusion: Addressing the Bottom Line -- 9.13 Companies Reap the Benefits of Analytics -- 9.14 A Project Risk Assessment Model -- 9.14.1 Project Property Measurements -- 9.14.2 A Project Risk Assessment System -- 9.14.3 Parameter Similarity Measurements -- 9.14.4 Learning from Our Mistakes -- 9.15 Risk Assessment and Cost Management -- 9.15.1 Defining What Constitutes as Risky Behavior Is Important -- 9.16 Risk Analysis Techniques -- 9.16.1 Risk Analysis Process -- 9.16.2 Disaster Prevention -- 9.16.3 Security and Control Considerations -- 9.16.4 Insurance Considerations -- 9.16.5 Records -- 9.16.6 Conclusion -- References -- Chapter 10: What Is Data Analysis from Data Warehousing Perspective? -- 10.1 Introduction -- 10.2 Data Mining and Data Modeling -- 10.2.1 Data Warehousing Concepts -- 10.2.2 Data Warehousing and Data Integrity -- 10.2.3 Data Warehousing and Business Intelligence -- 10.2.4 Data Warehousing and Master Data Management -- 10.2.5 Master Data Management vs. Data Warehousing -- 10.3 Big Data: What It Is and Why It Matters -- 10.4 Data Mining and Data Analysis in Real Time -- 10.5 Common Use Cases for Real-Time Technologies and Practices -- 10.6 Real-Time Data, BI, and Analytics Summary -- References -- Chapter 11: Boolean Computation Versus Fuzzy Logic Computation -- 11.1 Introduction -- 11.2 What Is Intelligence? -- 11.3 Can Computers Be Intelligence? -- 11.4 Difference Between Computational and Artificial Intelligence -- 11.5 The Five Main Principles of CI and Its Applications -- 11.6 Boolean Logic Versus Fuzzy Logic -- References -- Chapter 12: Defining Threats and Critical Points for Decision-Making -- 12.1 Introduction -- 12.2 Why Decision-Making Is Important -- 12.3 How to Make Better Decisions and Solve Problems Faster -- 12.3.1 The Importance of Problem-Solving.
12.3.2 Critical Thinking in the Decision-Making Process.
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Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
TK7885.Z64 2017 (Browse shelf) http://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=4814250 Available EBC4814250

Intro -- Dedication -- Preface -- Acknowledgments -- Contents -- About the Authors -- Chapter 1: Resilience and Resilience System -- 1.1 Introduction -- 1.2 Resilience and Stability -- 1.3 Reactive to Proactive Safety Through Resilience -- 1.4 The Business Resilience System Backdrop -- 1.5 Risk Atom Key Concept -- 1.6 Business Resilience System Features -- 1.7 Business Resilience System Project Plan -- 1.8 Summary of Business Resilience System -- References -- Chapter 2: Building Intelligent Models from Data Mining -- 2.1 Introduction -- 2.2 Risk Assessment and Risk Element -- 2.2.1 How the Risk Is Determined -- 2.2.2 Acceptable Risk Increase -- 2.2.3 Acceptable Risk in Auditing -- 2.2.4 Risk Analysis Process -- 2.3 Incident Response -- 2.3.1 What Is Incident Response -- 2.3.2 Real-Life Incidents -- 2.3.3 Incident Response Planning Program -- 2.3.3.1 Establishing the Incident Response Program -- 2.3.4 Tools of the Trade -- 2.3.5 What Is Out There -- 2.3.6 Risk Assessment and Incident Response -- 2.4 Predictive Modeling -- 2.4.1 Prediction in Enterprise Management -- 2.4.2 The Benefits and Predictive Modeling Basics -- 2.4.3 Basic Infrastructure of Modeling -- 2.4.4 Models and Event State Categorization -- 2.4.5 Model Type and Outcome Categorization -- 2.4.6 Critical Feature Selection for Predictive Models -- 2.4.7 Core Features of Robust Predictive Models -- 2.4.8 Model Type Selection -- 2.4.9 Basic Principles of Predictive Models -- References -- Chapter 3: Event Management and Best Practice -- 3.1 Introduction to Event Management -- 3.2 Event Management Terminology -- 3.2.1 Event -- 3.2.2 Event Management -- 3.2.3 Event Processing -- 3.2.4 Automation and Automated Actions -- 3.3 Concepts and Issues -- 3.3.1 Event Flow -- 3.3.2 Filtering and Forwarding -- 3.3.3 Duplicate Detection and Throttling -- 3.3.4 Correlation.

3.3.5 Event Synchronization -- 3.3.6 Notification -- 3.3.7 Trouble Ticketing -- 3.3.8 Escalation -- 3.3.9 Maintenance Mode -- 3.3.10 Automation -- 3.4 Planning Considerations -- 3.4.1 IT Environment Assessment -- 3.4.2 Organizational Considerations -- 3.4.3 Policies -- 3.4.4 Standards -- Reference -- Chapter 4: Event Management Categories and Best Practices -- 4.1 Introduction -- 4.2 Implementation Approaches -- 4.2.1 Send All Possible Events -- 4.2.2 Start with Out-of-the-Box Notifications and Analyze Reiteratively -- 4.2.3 Report Only Known Problems and Add Them to the List as They Are Identified -- 4.2.4 Choose Top X Problems from Each Support Area -- 4.2.5 Perform Event Management and Monitoring Design -- 4.3 Policies and Standards -- 4.3.1 Reviewing the Event Management Process -- 4.3.2 Defining Severities -- 4.3.3 Implementing Consistent Standards -- 4.3.4 Assigning Responsibilities -- 4.3.5 Enforcing Policies -- 4.4 Filtering -- 4.4.1 Why Filter -- 4.4.2 How to Filter -- 4.4.3 Where to Filter -- 4.4.4 What to Filter -- 4.4.5 Filtering Best Practices -- 4.5 Duplicate Detection and Suppression -- 4.5.1 Suppressing Duplicate Events -- 4.5.2 Implications of Duplicate Detection and Suppression -- 4.5.3 Duplicate Detection and Throttling Best Practices -- 4.6 Correlation -- 4.6.1 Correlation Best Practice -- 4.6.2 Implementation Considerations -- 4.7 Notification -- 4.7.1 How to Notify -- 4.7.2 Notification Best Practices -- 4.8 Escalation -- 4.8.1 Escalation Best Practices -- 4.8.2 Implementation Considerations -- 4.9 Event Synchronization -- 4.9.1 Event Synchronization Best Practices -- 4.10 Trouble Ticketing -- 4.10.1 Trouble Ticketing -- 4.11 Maintenance Mode -- 4.11.1 Maintenance Status Notification -- 4.11.2 Handling Events from a System in Maintenance Mode -- 4.11.3 Prolonged Maintenance Mode -- 4.11.4 Network Topology Considerations.

4.12 Automation -- 4.12.1 Automation Best Practice -- 4.12.2 Automation Implementation Considerations -- 4.13 Best Practices Flowchart -- Reference -- Chapter 5: Dynamic and Static Content Publication Workflow -- 5.1 Introduction -- 5.2 Business Workflow -- 5.2.1 Workflow Management -- 5.2.2 Business Rules Engine -- 5.2.3 Business Rules Platform -- 5.2.4 Business Transformation -- 5.3 Dynamic Publishing and Processes -- 5.4 E-commerce World and Dynamic Content Publication Workflow -- 5.5 Overall Concepts/Philosophy -- 5.6 Business Resilience System Technology Topology Design -- 5.6.1 Terms and Definitions -- 5.6.2 Architecture Diagram and Logical Architecture -- 5.6.3 Publication Process and Actors and Workflow -- 5.6.4 Static Content Publication Workflow -- 5.6.5 Product Image Data Storage -- 5.6.6 Product Image Data Publishing and Editing -- 5.6.7 Transaction Data Management Process -- 5.6.8 Hardware/Software Specifications -- 5.6.9 Webmail and Discussion Board Interface -- 5.6.10 Member Address Book -- 5.6.11 Site and Database Search -- 5.6.12 Load Balancing and Web Farm Management -- 5.7 System Interfaces -- 5.8 Technical Approach -- 5.8.1 Technical Requirements for Phase I -- 5.8.2 Technical Requirements Beyond Scope for Phase I -- 5.8.3 Proposed Hardware and Network Architecture (Fig. 5.9) -- 5.8.4 Logical Architecture for Live Environment -- 5.8.5 Technical Risks -- 5.8.5.1 Phase I Items Not Estimated -- 5.8.5.2 Recommended Solution -- 5.8.5.3 User Home Pages -- References -- Chapter 6: What Is Boolean Logic and How It Works -- 6.1 Introduction -- 6.2 How Bits and Bytes Work -- 6.2.1 The Base-2 System and the 8-Bit Byte -- 6.2.2 The Standard ASCII Character Set -- 6.2.3 Byte Prefixes and Binary Math -- 6.3 Logical Gates -- 6.4 Simple Adders -- 6.5 Full Adders -- 6.6 Truth Tables -- 6.6.1 Practical Truth Tables -- 6.7 Summary -- Reference.

Chapter 7: What Is Fuzzy Logic and How It Works -- 7.1 Introduction -- 7.2 What Is Fuzzy Logic -- 7.3 Fuzzy Logic and Fuzzy Sets -- 7.4 The Fuzzy Logic Method -- 7.4.1 Fuzzy Perception -- 7.4.2 Novices Can Beat the Pros -- 7.4.3 A Milestone Passed for Intelligent Life on Earth -- 7.4.4 Fuzzy Logic Terms Found in Books and Articles -- 7.5 The World's First Fuzzy Logic Controller -- 7.5.1 Progress in Fuzzy Logic -- 7.5.2 Fuzzy Logic Control Input: Human and Computer -- 7.5.3 More About How Fuzzy Logic Works -- 7.6 Rationale for Fuzzy Logic -- Reference -- Chapter 8: Mathematics and Logic Behind Boolean and Fuzzy Computation -- 8.1 Mathematics of Boolean Logic and Algebra -- 8.1.1 Definition and Simple Properties -- 8.1.2 Special Classes of Boolean Algebras -- 8.1.3 Structure Theory and Cardinal Functions on Boolean Algebras -- 8.1.4 Decidability and Undecidability Questions -- 8.1.5 Lindenbaum-Tarski Algebras -- 8.1.6 Boolean-Valued Models -- 8.2 Mathematics of Fuzzy Logic -- 8.2.1 More Description of Mathematics of Fuzzy -- References -- Chapter 9: Building Intelligent Models from Data Mining and Expert Knowledge -- 9.1 Introduction -- 9.2 Introduction to Predictive Modeling -- 9.2.1 Simple Linear Regression -- 9.3 Knowledge-Based Models -- 9.4 Knowledge, Intelligence, and Models -- 9.5 Model Development and Protocycling -- 9.6 Subject Matter Experts and Acquired Knowledge -- 9.7 The Methodology -- 9.8 Fuzzy Knowledge Bases for Business Process Modeling -- 9.9 Risk Assessment Model -- 9.9.1 Setting High Goals and Exceeding Them -- 9.9.2 Defining the Problem -- 9.9.3 Moving Beyond Log Management and Security Software -- 9.9.4 Expanding the Approach with Sense Analytics -- 9.10 Risk and Vulnerability Management -- 9.10.1 Threat Detection -- 9.10.2 Forensics Investigation -- 9.10.3 Incident Response -- 9.10.4 Regulatory Compliance.

9.11 Keeping Up with Evolving Threats and Risks -- 9.12 Conclusion: Addressing the Bottom Line -- 9.13 Companies Reap the Benefits of Analytics -- 9.14 A Project Risk Assessment Model -- 9.14.1 Project Property Measurements -- 9.14.2 A Project Risk Assessment System -- 9.14.3 Parameter Similarity Measurements -- 9.14.4 Learning from Our Mistakes -- 9.15 Risk Assessment and Cost Management -- 9.15.1 Defining What Constitutes as Risky Behavior Is Important -- 9.16 Risk Analysis Techniques -- 9.16.1 Risk Analysis Process -- 9.16.2 Disaster Prevention -- 9.16.3 Security and Control Considerations -- 9.16.4 Insurance Considerations -- 9.16.5 Records -- 9.16.6 Conclusion -- References -- Chapter 10: What Is Data Analysis from Data Warehousing Perspective? -- 10.1 Introduction -- 10.2 Data Mining and Data Modeling -- 10.2.1 Data Warehousing Concepts -- 10.2.2 Data Warehousing and Data Integrity -- 10.2.3 Data Warehousing and Business Intelligence -- 10.2.4 Data Warehousing and Master Data Management -- 10.2.5 Master Data Management vs. Data Warehousing -- 10.3 Big Data: What It Is and Why It Matters -- 10.4 Data Mining and Data Analysis in Real Time -- 10.5 Common Use Cases for Real-Time Technologies and Practices -- 10.6 Real-Time Data, BI, and Analytics Summary -- References -- Chapter 11: Boolean Computation Versus Fuzzy Logic Computation -- 11.1 Introduction -- 11.2 What Is Intelligence? -- 11.3 Can Computers Be Intelligence? -- 11.4 Difference Between Computational and Artificial Intelligence -- 11.5 The Five Main Principles of CI and Its Applications -- 11.6 Boolean Logic Versus Fuzzy Logic -- References -- Chapter 12: Defining Threats and Critical Points for Decision-Making -- 12.1 Introduction -- 12.2 Why Decision-Making Is Important -- 12.3 How to Make Better Decisions and Solve Problems Faster -- 12.3.1 The Importance of Problem-Solving.

12.3.2 Critical Thinking in the Decision-Making Process.

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