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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.
Information Systems CoreCourse 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 ManagementModule 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 AnalyticsModule 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 StewardshipModule 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 WarehouseModule 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 ManagementModule 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 QualityModule 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 |