​Online Courses run 3 times per year: During the weeks of: Jan 19; June 17, Sept 20. Weekly meeting day and time will be communicated by the instructor prior to start.
  1.  Information Systems Core
  2.  Business & Technology Management
  3.  Business Intelligence & Data Analytics 
  4.  Data Modeling (Data Development)
  5. ​ Data Foundations
  6.  Data Governance & Stewardship
  7.  Data Management
  8.  ​Data & Information Quality
  9.  Data Science
  10.  Data Warehousing
  11.  IS Management
  12.  Systems Development (Systems Analysis & Design)

Information Systems Core

Course Summary:
Module 1: Information Systems, Role, Standards, Business Drivers, Strategies
Module 2: Enterprise Architecture
Module 3: Hardware Software and Network Infrastructure
Module 4: Internet and WWW
Module 5: e-Commerce
Module 6: Project Management
Module 7: Systems Development
Module 8: Application and System Types
Module 9: Data Management
Module 10: Data Modeling
Module 11: Decision Support and Business Intelligence
Module 12: Ethics, Privacy and Security

Textbook: ​
​Management Information Systems for the Information Age by Stephen Haag and Maeve Cummings, McGraw Hill Higher Education; 9th (international) edition, 2012. ISBN 10: 0071314644 / 0-07-131464-4; ISBN 13: 9780071314640.  ​and can be purchased through www.amazon.com.

Data Management

Module 1: Data Management Process
Module 2: Data Governance Function
Module 3: Data Architecture Management Function
Module 4: Data Development Function
Module 5: Data Operations Management Function
Module 6: Data Security Function
Module 7: Reference and Master Data Management Function
Module 8: Data Warehousing and Business Intelligence Management Function
Module 9: Document and Content Management Function
Module 10: Meta-Data Management Function
Module 11: Data Quality Management Function
Module 12: Professional Development
Textbook:
The textbook is extra and can be purchased through technicspub.com 
2nd Edition 2017 DMBoK V2. There is also a companion DAMA Dictionary, available through technicspub.com. ​These are also available thru Amazon.com.
Big Data Online Course
​Module 1: Big Data Terminology (7)
  1.1.0 Volume, Velocity, Variety, Variability, Veracity, Visualization, and Value
  1.2.0 Multi-structured data
    1.2.1 Structured data
    1.2.2 Unstructured data (Data Lakehouse)
    1.2.3 Disambiguated Data
 Module 2: 1.3.0 Data Ingestion
    1.3.1 Internal, external, third party
    1.3.2 Social media (Facebook, Twitter, Snapchat, Pinterest, Instagram, Vine, etc.)
    1.3.3 Streaming
    1.3.4 IOT/sensors/instrumentation
    1.3.5 Activity based: specific e.g. sports, non-specific – activity versus inactivity
    1.3.6 Health/Medicine
  1.4.0 Big Data Frameworks and Tools
Module 3, 4, 5, 6, 7  Big Data Concepts (89)
Module 3:  
    2.1.0 Preparation, Storage, Discovery, Search, Navigation
    2.1.1 Rapid retrieval and analysis
    2.1.2 Associative logic
Module 4:
    2.2.0 Land Data (Access, Collect), Manage, Store
    2.3.0 Multi-source integration
Module 5:  
    2.4.0 Big Data Analytics 
    2.4.1 Data Mining
    2.4.2 Cognitive Computing
    2.4.3 Forecast versus Now-cast
Module 6:  
    2.4.4 Complex Event Processing
    2.4.5 Location Based Services
    2.4.6 Mathematical & Statistical Techniques
    2.4.7 Classification and Regression
 Module 7: 
    2.4.8 Machine Learning/Artificial Intelligence
    2.4.9 Supervised and Non-Supervised Learning
    2.4.10 Algorithms and estimation
    2.4.11 Predictive models
  2.5.0 Structured controlled data
Module 8:
  2.6.0 Analyzing unstructured data
  2.7.0 Real time (Streaming data analytics)
  2.8.0 Full Contextual Analysis
  2.9.0 Textual Disambiguation
 Module 9:
  2.10.0 Big Data Integration
  2.11.0 Models, building and validating
  2.12.0 Data Visualization
Module 10, 11 Technical Considerations (10)
Module 10:
  3.1.0 Storage methods, technologies, volume and relationships
  3.2.0 Data Architecture
  3.3.0 Data Ingestion Requirements
  3.4.0 Infrastructure considerations
    3.4.1 In memory analytics
    3.4.2 Analytical tools
  3.5.0 Feature extraction and metadata
  3.6.0 Consistency/Redundancy
Module 11:  
    3.7.0 Implementation considerations
    3.7.1 Data store location (internal, external, hybrid)
    3.7.2 Archiving
  3.8.0 Operational Considerations
    3.8.1 R, Python, and other languages
Module 12:
4.0.0 Big Data Governance sources, data quality, integration, security, life cycle, master-data-management & definitions (4)
  4.1.0 Organizational Structures and Awareness
    4.1.1 Information as a Service (IaaS):
    4.1.2 Platform as a Service (PaaS)
    4.1.3 Software as a Service
  4.2.0 Stewardship
    4.2.1 Data Quality management
  4.3.0 Policy
  4.4.0 Value Creation
  4.5.0 Fit of Data
    4.5.1 For purpose (Line of Business)
    4.5.2 Trusted
  4.6.0 Data Risk Management & Compliance
    4.6.1 Acceptable use
    4.6.2 Depth of insight
    4.6.3 Data Security
    4.6.4 Retention requirements
  4.7.0 Information Security & Privacy
    4.7.1 Personal identification information
    4.7.2 Unique identification data
    4.7.3 Right to be forgotten – issues of ownership
    4.7.4 Data masking
  4.8.0 Data Quality management
  4.9.0 Classification and metadata
  4.10.0 Information lifecycle management
  4.11.0 Audit information, logging and reporting

Textbook: David Loshin, Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph 1st Edition
Additional Text: Learning Spark: Lightning-Fast Data Analytics 2nd Edition by Jules S. Damji  (Author), Brooke Wenig (Author), Tathagata Das (Author), Denny Lee (Author)
Blockchain Technical 
​Module 1. Introduction to Blockchain
       · Concepts
        · Use Cases
        · Technical Features and Capabilities
        · Public vs Private Initiatives 
        · Security
        · Platform, Vendor, Sourcing, and Organizational Considerations
Module 2 and 3. Blockchain Use Cases
        · Blockchain vs Cryptocurrencies (e.g., Bitcoin)
        · Cross Industry Examples
        · Industry Specific Examples
        · Blockchain Technical Use Cases
        · Mining Blockchain
Module 4 and 5. Cryptocurrency
       · Technical Considerations for Cryptocurrency
       · Understanding & Selecting the Right Cryptocurrency Platform
       · Concept of Opening Cryptocurrency Wallets
       · Buying Cryptocurrency Wallets
       · Programming Languages and Considerations 
       · Withdrawal Cryptocurrency Wallets
Module 6. Blockchain: Beyond Cryptocurrency
       · Industry Specific Use Cases
       · Selecting the right technology/platform, and vendor for the initiative
              o Kind of Network
              o Programming Languages Available and Considerations
              o Popularity
              o Activity
              o Pricing
              o Flexibility and Consensus Mechanisms
Module 7 and Module 8. Blockchain Technology/Product (e.g., Bitcoin, Ethereum, Hyperledger, IBM, Multichain, Hydrachain, Ripple, R3 Corda, BigChainDB, Open-chain, IOTA) Use Cases
       · Technology Choices & Uses Introduction
       · Blockchain vs Bitcoin
       · Technology Features
       · Smart Contracts
       · Technology Installation
       · Technology Accounts
       · Technology Virtual Machine
       · Deploying Smart Contracts
       · Smart Contracts and DAOs (Decentralized Autonomous Corporation)
       · Decentralize MJ Apps/Platforms (Enable Preventative Compliance, Precise Inventory Visibility, and Streamlined Operations.
Module 8 and 9. Technical Deployment (Focus On One to Two Platforms e.g., Bitcoin, Ethereum, Hyperledger, IBM, Multichain, Hydrachain, Ripple, R3 Corda, BigChainDB, Open-chain, IOTA) Details
       · Comparison of Platform Features and Capabilities
       · Fundamentals of the Technology
       · Technology Architecture and Integration
       · Blockchain vs the Technology
       · Technology Programming Considerations and Details
Module 10 and 11.  Project Industry Examples and Use Cases
       · Voting with Blockchain
       · Business Network Implementation.
       · Smart Contract for SCM (Supply Chain Management) Network
       · Smart Contract for Letter of Credit
       · Industry Specific Applications and Use Cases
Module 12: Internal and External Blockchains
       · Mining internal blockchains and technical considerations
       · Mining external blockchains and technical considerations
       · Data Security and Ransomware Protection

Prerequisites:  Working knowledge of internet, networking & programming knowledge.  
Textbook: Mastering Blockchain: Unlocking the Power of Cryptocurrencies, Smart Contracts, and Decentralized Applications 1st Edition by Lorne Lantz  (Author), Daniel Cawrey  (Author), Orielly Press.
Alternate Text: Cryptographic Primitives in Blockchain Technology: A mathematical introduction by Andreas Bolfing (Author), Oxford Press.

Business Intelligence & Data Analytics

Module 1: BI Concepts
Module 2: BI Current State Considerations
Module 3: Infrastructures and Tool Functional Areas
Module 4: BI and Data Management
Module 5: BI and Organizational Roles
Module 6: Corporate Performance Management
Module 7: Inputs for Decision Making
Module 8: Analytics Techniques
Module 9: BI Justification
Module 10: Evaluation and Selection of a BI Platform and Tool
Module 11: BI Solution Lifecycle
Module 12: Additional areas for BI Consideration
Textbook:
​The New Era of Enterprise Business Intelligence: Using Analytics to Achieve a Global Competitive Advantage by Mike Biere, IBM Press, 2011. ISBN-10: 0-13-707542-3, ISBN-13: 978-0-13-707542-3 available through www.amazon.com. ​​
Data Foundations
Module 1: Introduction to data foundations
Module 2: Database Development
Module 3: Introduction to Data Foundations II
Module 4: Introduction to Data Foundations II Cont'd.
Module 5: Data Administration
Module 6: Data Administration Cont'd.
Module 7: Database and Repository Management
Module 8: Data Management Environment
Modules 9-12: Database Management Environment Cont'd.

Course Textbook and Other Resources

Principles of Data Management: Facilitating Information Sharing, 2nd Edition, Keith Gordon (2013), BCS Learning and Development Ltd. ISBN -978-1-78017-184-5; PDF ISBN -978-1-78017-185-2

Data Governance and Stewardship

Module 1: Data Governance and Stewardship Core Concepts
Module 2: Data Governance Program Overview
Module 3:Data Governance Program Business Case
Module 4:Data Governance Deployment Methodology: Part I
Module 5:Data Governance Program Deployment Methodology: Part II
Module 6: Data Stewardship Role Types, Basic Duties, Artifacts, and Tools
Module 7: Data Stewardship Activities: Data Architecture Focus and Data Development Focus
Module 8: Data Stewardship Activities: Data Operations Focus and Data Security Focus
Module 9: Data Stewardship Activities: Data Integration and Interoperability Focus, and Document and Content Focus
Module 10:  Data Stewardship Activities: Reference and Master Data Management Focus and Data Warehousing / Business Intelligence Focus
Module 11:Data Stewardship Activities; Metadata and Data Quality Focus
Module 12: Additional Data Governance and Stewardship Considerations
The textbook is extra and can be purchased through www.amazon.com at new or various used or e-reader prices.  Ladley, John, DATA GOVERNANCE: HOW TO DESIGN, DEPLOY, AND SUSTAIN AN EFFECTIVE DATA GOVERNANCE PROGRAM, Morgan Kaufman,  Nov 2019  and DAMA International, THE DAMA GUIDE TO THE DATA MANAGEMENT BODY OF KNOWLEDGE (DAMA-DMBOK2), Technics Publications, 2017 at www.technicspub.com/dmbok/

Data Warehouse

Module 1: Data Warehousing (DW) and Business Intelligence (BI) Concepts
Module 2: DW and BI Use
Module 3: DW Management
Module 4: DW Roles
Module 5: DW Architectures
Module 6: DW & BI tech. architecture
Module 7: DW Analysis
Module 8: DW Modeling & Design
Module 9: Data Management Process Relationship
Module 10: DW Development
Module 11: BI Application Development Activities
Module 12: DW Implementation & Enchancement
Textbook:
TextbookThe textbook is extra and can be purchased through  www.amazon.com  at $37.74 USD new or at various used or e-reader prices: A Manager’s Guide to Data Warehousing by Laura L. Reeves, Wiley, 2009. ISBN-10: 0470176385, ISBN-13: 978-0470176382. ​

Information Systems Management

Module 1: Management and Information Systems Concepts
Module 2: Strategy Models
Module 3: Strategic Use of Information Resources
Module 4: IT, Organizational Design and Management Control
Module 5: Technology and Work Design
Module 6: Business Process Management (BPM)
Module 7: Strategy, Architecture and Infrastructure
Module 8: IT/IS Sourcing
Module 9: IT Governance and Ethics
Module 10:  IT Funding
Module 11: Project Management
Module 12: Data, Information, Knowledge Management and Business Analytics
Textbook
​​The textbook is extra and can be purchased through www.amazon.com at new or various used or e-reader prices. Managing and Using Information Systems by Keri E. Pearlson and Carol S. Saunders, Pearson Education Inc. (John Wiley & Sons), 4th edition, copyright 2010 and 2012 (A Strategic Approach), published Jan. 14, 2009, ISBN-10: 047034343818, ISBN-13: 978-0-470-34381-4.

Systems Development (Systems Analysis & Design)

Module 1: Systems Concepts and Roles
Module 2: Systems Development Approaches
Module 3: Project Management Process, Methodologies, & Techniques
Module 4: Systems Project Planning
Module 5: Systems Requirements Determination
Module 6: Systems Process Requirements Structuring
Module 7: Systems Data Requirements Structuring
Module 8: Logical & Physical Design
Module 9: Designing Forms, Reports, Interfaces and Dialogues
Module 10: Distributed and Internet systems considerations & Documentation
Module 11: Implementation Considerations
Module 12: Maintenance Considerations
Textbook:
The textbook is extra and can be purchased through www.amazon.com at new or various used or e-reader prices. Modern Systems Analysis and Design by Jeffrey A. Hoffer, Joey George and Joe Valacich, Pearson Education Inc. and any new SAD Systems Analysis and Design by Alan Dennis, Barbara Wixom, et al. | Dec 27, 2018  available on amazon.com

Data & Information Quality

Module 1: DIQ Issues, Definitions and Importance
Module 2: Quality approaches and relationships to information
Module 3: Data Quality Frameworks: Methodology, Maturity Models, QM Awards
Module 4: Assessment: Data Definition and Information Architecture Quality
Module 5: Assessment DIQ
Module 6: Measurement Poor Quality Information Costs
Module 7: Information Improvement: Data Cleansing
Module 8: Information Process Improvement: data defect prevention
Module 9: DIQ Tools & Techniques
Module 10: DG Governance Function & Stewardship
Module 11: Implementation: DIQ Environment
Module 12: DIQ - Sustainment, Monitoring, Metrics Reporting

Textbook:
​The textbook is extra and can be purchased through www.amazon.com  Improving Data Warehouse and Business Information Quality by Larry P. English, Wiley, 1999, ISBN-10: 0471253839; ISBN-13: 978-0471253839
Phone: 1.800.843.8227, 1.847.299.4227  email: office2@iccp.org 
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