COURSE DESCRIPTION
Sustainable success is contingent upon an organization’s capability to be agile and innovative with its data. Businesses are in dire need of IT professionals and Project Managers who possess adequate data management skills. It is estimated that by year 2017, the data management market will expand to $50 billion, while the need for skilled managers and analysts for data management projects will grow to 1.5 million. This would mean higher demand and salary for project managers and analysts specialized in data related projects.
| Majd Izadian is a Data, Information, and Knowledge management professional with over 25 years of industry experience in Healthcare, Supply Chain, High Tech, Real Estate, Finance, and Oil & Gas. He has held executive positions in Fortune 5, Fortune 67, and Fortune 500 companies with both domestic and international clienteles such as UnitedHealth Group, Kaiser Permanente, Ingram Micro, Huawei, Cisco, Corvel, Hong Kong Police, and many others. He has a patent in data management technologies and has innovated numerous novel frameworks and methodologies. Majd has taught at the University of California in Irvine as an Adjunct Professor in Data Science courses. Majd is currently the Chief Data Officer and managing partner at Xendat Data & Analytics. |
LEARNING OUTCOMES
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- Fundamentals of Data Management
- MDM, Data Quality, Big Data, BI, Data Governance, And Other Data Projects Requirements
- Enterprise Projects Impacting Data
- Data Management Tasks in Project Lifecycle
- Roles & Responsibilities in Data Projects
- Working with Data Governance Organizations
- Ensuring On Time, On Budget Data Projects
- Managing Risks in Data Projects
- Data Stakeholder Management
- Data Projects Governance
- Lectures 76
- Quizzes 6
- Duration 3 hours
- Skill level All levels
- Language English
- Students 275
- Assessments Yes
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Introduction to Data
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Data classifications
- DATA CLASSIFICATIONS INTRO
- DATA CLASSIFICATIONS TYPES
- WHAT IS MASTER DATA?
- WHY MASTER DATAMANAGEMENT
- USING A CANONICAL MODEL IN MDM
- MDM BEST PRACTICES
- MANAGING MASTER DATA ACROSS MULTI PROCESSES
- REPORTING DATA
- FACTS VS. TRUTH IN DATA
- SINGLE VERSION OF TRUTH
- BUSINESS INTELLIGENCE REPORTING
- BIG DATA
- BIG DATA SEGMENTATION
- Quiz 2- Data Classifications
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Managing Data Part 1
- DATA AFFINITY
- DATA LIFECYCLE
- DATA INTEGRATION VS. MIGRATION
- INFORMAL DATA INTEGRATION
- FORMAL DATA INTEGRATION
- DATA LINEAGE
- DATA QUALITY
- DATA QUALITY DIMENSIONS
- DATA DISSEMINATION IMPACT ON DATA QUALITY
- REACTIVE DATA QUALITY
- PROACTIVE DATA QUALITY
- XENDAT DQ METHODOLOGY
- DQ REQUIREMENTS: COMPLETENESS EXAMPLE
- DQ REQUIREMENTS: VALIDITY EXAMPLE
- Quiz 3- Managing Data- Part 1
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Managing Data Part 2
- DATA GOVERNANCE AND STEWARDSHIP
- DATA STEWARDSHIP VS. OWNERSHIP
- POLICIES IN DATA GOVERNANCE
- DATA POLICIES
- DATA GOVERNANCE PRINCIPALS
- DATA GOVERNANCE MODELS
- DATA GOVERNANCE DIMENSIONS
- DATA GOVERNANCE ROLES
- FEDERATED DATA GOVERNANCE ORGANIZATION
- OBJECTIVES OF THE EDMO
- EDMO RESPONSIBILITIES
- DMO RESPONSIBILITIES
- EDMO RESPONSIBILITIES SCOPE
- DATA GOVERNANCE FUNCTIONAL MATRIX
- DATA GOVERNANCE PROCESS LEVELS
- Quiz 4- Managing Data- Part 2
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Data Project Basics
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Data Project plc
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Data Project Risk Management
- POINTS OF FAILURE ANALYSIS EXAMPLE
- POINTS OF FAILURE ANALYSIS TEMPLATE
- DATA DEFINITION TEMPLATE
- DATA AFFINITY ANALYSIS
- DATA AND PROCESS AFFINITY ANALYSIS- EXAMPLE
- DATA TO SYSTEMS AFFINITY TEMPLATE
- SYSTEM TO PROCESS AFFINITY ANALYSIS- EXAMPLE
- DATA LINEAGE ANALYSIS EXAMPLE
- DATA PROJECT GOVERNANCE MODEL
