Enterprise Big Data Professional
Enterprise Big Data Professional
An Introduction to Big Data and Data Science for the Enterprise
About the Book
The book Enterprise Big Data Professional offers a comprehensive introduction to the essential techniques and concepts of Big Data. It covers fundamental principles and methodologies that are critical for understanding and working with large-scale data systems. By delving into topics such as data processing frameworks, storage solutions, and analytical techniques, the book equips readers with the foundational knowledge needed to navigate the complex landscape of Big Data.
In addition to providing a broad overview of Big Data concepts, the book serves as the official study guide for the APMG International certification program. This ensures that readers are not only learning key principles but also preparing effectively for the certification exam. As the designated study resource, Enterprise Big Data Professional aligns closely with the certification requirements, offering targeted insights and practice material to help candidates succeed in their pursuit of becoming certified Big Data professionals.
About the Author
Table of Contents
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Colophon
- Purpose
- Important Note
- Trademarks
- About the Enterprise Big Data Framework Alliance
- The Big Data Certification Scheme
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Forewords
- Foreword by Richard Pharro
- Foreword by Jan-Willem Middelburg
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1. Introduction to Big Data
- 1.1 What is Big Data?
- 1.2 Value of Big Data
- 1.3 A Short History of Big Data
- 1.4 Big Data Characteristics
- 1.5 Data Analysis, Analytics, Data Science, BI and Big Data
- 1.6 Data Structures
- 1.7 Data Products and Big Data Solutions
- 1.8 Artificial Intelligence
- 1.9 Machine Learning
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2. The Enterprise Big Data Framework
- 2.1 Why an Enterprise Big Data Framework?
- 2.2 The Structure of the Enterprise Big Data Framework
- 2.3 Working with the Enterprise Big Data Framework
- 2.4 Big Data Maturity Assessment
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3. Big Data Strategy
- 3.1 Big Data as Competitive Strategy
- 3.2 Business Drivers for Big Data
- 3.3 Formulating a Big Data strategy
- 8.4 The Big Data Strategy Document Checklist
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4. Big Data Architecture
- 4.1 Introduction to Big Data architecture
- 4.2 The NIST Big Data Reference Architecture
- 4.3 Distributed Data Storage and Processing
- 4.4 Big Data Storage
- 4.5 Big Data Analysis Architecture
- 4.6 Hadoop Open Source Software Framework
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5. Big Data Algorithms
- 5.1 Introduction to Algorithms
- 5.2 Desciptive Statistics
- 5.3 Statistical Inference
- 5.4 Correlation
- 5.5 Regression
- 5.6 Classification
- 5.7 Clustering
- 5.8 Outlier Detection
- 5.9 Data Visualization
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6. Big Data Processes
- 6.1 Introduction to Big Data Processes
- 6.2 Data Analysis Process
- 6.3 Data Governance Process
- 6.4 Data Management Process
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7. Big Data Functions
- 7.1 Introduction to Big Data Functions
- 7.2 Designing a Big Data Organization
- 7.3 Roles and Responsibilities in Big Data Teams
- 7.4 Big Data Skills
- 7.5 Organizational Success Factors for Big Data
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8. Artificial Intelligence
- 8.1 Introduction to Artificial Intelligence
- 8.2 Artificial Intelligence in the Enterprise
- 8.3 Cognitive Analytics
- 8.4 Capabilities in Artificial Intelligence
- 8.5 Deep Learning
- 8.6 Next Steps
- Glossary
- Notes
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