The Intelligent Enterprise in the Era of Big Data

Venkat Srinivasan






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An innovative guide to the organization and function of enterprises in the technological age

In the era of big data and automation, this book presents a cutting-edge approach in how enterprises should organize and function. Striking a practical balance between theory and practice, The Intelligent Enterprise in the Era of Big Data presents an enterprise architecture that embodies the power of the emerging technology environment.

Beginning with an introduction to the key challenges that enterprises face, the book systematically outlines a modern enterprise architecture through a detailed discussion of the inseparable elements of such an architecture: efficiency, flexibility, and intelligence. This architecture enables rapid responses to market needs by facilitating intelligent, flexible automation of enterprise business processes and sensing important developments in internal and external environments in near real time. Illustrating all of these elements in an integrated fashion, The Intelligent Enterprise in the Era of Big Data also features:

  • A detailed discussion on issues of time-to-market and flexibility with respect to enterprise application technology
  • Novel analyses illustrated through extensive real-world case studies to help readers better understand the applicability of the architecture and concepts
  • Practical approaches for designing and building intelligent enterprises 
  • An appendix that presents various approaches to text analysis with real-world business implications
The Intelligent Enterprise in the Era of Big Data is an appropriate reference for business executives, information technology professionals, data scientists, and management consultants. 

Chapter 1: The Crisis Has Not Gone Away; Opportunity Beckons

1.1 Introduction

1.2 The Challenge with Current Technology Paradigms: Chronic issues of time to market and flexibility

1.3 Emergence of Packaged Applications

1.4 The New Front: Information; Big Data is not new; what is new is unstructured information

1.5 Enterprise Architecture: Current State and Implications

1.6 The Intelligent Enterprise of Tomorrow – Opportunity Beckons


Chapter 2: Efficiency and Agility

2.1 Introduction

2.2 The Process-Oriented Enterprise

2.2.1 Becoming Process Oriented

2.2.2 Why do we have to choose?

2.2.3 Design and Execution

2.3 The Role of Outsourcing in Creating Efficiency and Agility

2.4 The Role of Technology in Efficiency and Agility

2.4.1 Current challenges with technology

2.4.2 BPM Software

2.4.3 The Role of Methodology

2.4.3 Agile does not equal Agility

2.5 A New Technology Paradigm for Efficiency and Agility

2.5.1 Technology and the Process-Oriented Architecture

2.5.2 RAGE AI™

2.5.3 RAGE Abstract Components

2.5.4 RIM™ - An Actionable, Dynamic Methodology

2.5.5 Real Time Software Development

2.6 Summary


Chapter 3: Insight and Intelligence

3.1 Introduction

3.2 The Excitement around Big Data

3.3 Information Overload, Asymmetry and Decision Making

3.3.1 Information Overload

3.3.2 Information Asymmetry

3.4 Artificial Intelligence to the Rescue

3.4.1 A Taxonomy of AI Problem Types & Methods

3.4.2 Machine Learning Using Computational Statistics

3.4.3 Machine Learning with Natural Language

3.5 A Deep Learning Framework for Learning and Inference

3.5.1 Conceptual Semantic Network

3.5.2 Knowledge Discoverer

3.5.3 Computational Linguistics Engine

3.5.4 Impact Analysis

3.5 Summary


Chapter 4: The Intelligent Enterprise of Tomorrow

4.1 The Road to the Intelligent Enterprise

4.2 Enterprise Architecture Evolution

4.3 Enterprise 4.0 - The Intelligent Enterprise of Tomorrow

4.3.1 Availability of Information

4.4 Summary


Chapter 5: Active Advising with Intelligent Agents

5.1 Introduction

5.2 The Investment Advisory Market

5.3 What do Investors Really Need and Want

5.4 Challenges with High Touch Advisory Services

5.4.1 Questions of Value and Interest

5.4.2 The Massive ‘Wealth Transfer’ Phenomenon

5.4.3 The Rise of Robo-Advisors

5.4.4 Technology for HNWI’s Unique Needs

5.5 Active Advising – a Framework based on Machine Intelligence

5.6 Summary


Appendix A

Chapter 6: Finding Alpha in Financial Markets

6.1 Introduction

6.2 Information Asymmetry and Financial Markets

6.3 Machine Intelligence and Alpha

6.4 How well does it work?

6.4.1 Data

6.4.2 Measuring Lead-Lag Relationship

6.4.3 Back testing Results

6.5 Summary

Appendix A


Chapter 7: Will Financial Auditors Become Extinct?

7.1 Introduction

7.2 The External Financial Audit

7.2.1 Client Engagement

7.2.2 Audit Planning

7.2.3 Fieldwork

7.2.4 Review and Draft

7.3 An Intelligent Audit Machine

7.3.1 Client Engagement

7.3.2 Audit Planning

7.3.3 Fieldwork

7.3.4 Existence tests

7.3.5 Rights and Obligations

7.3.6 Substantive Analytical Procedures

7.3.7 Closing Balance Tests

7.3.8 Analyze and Issue Financials

7.3.9 Audit Standards

7.3.10 Workflow/Configuration

7.4 Summary


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