Intelligent CRM Metadata
Our Project Executive Summary Team and Management Goals

Our Project Goals
Our "Post Office (PO) (" Project and CRM Data Farm have a number of hardware and software components. Hardware is centered on building Data Centers with intelligent Building and Migration Editors. Virtualization is a key element in building and maintaining these Data Centers. The software components are all the cloud software system running these Data Centers. Big Data is stored in these Data Center and CRM is the engine which tailors Big Data into BI, Analytics, others services. Both hardware and software components requires management, security, support-labor, cloud governance, virtualization plus other details which run and support these Data Centers. We are building data or Big Data in these centers into independent-intelligent-services with Intelligent Data Access Objects (IDAO) and XML base format.

The Real World
To make our PO and CRM Data Farm a practical solutions for the real world with all its issues, our PO and CRM Data Farm must have a way to convert any existing data into our new IDAO-XML format. Our conversion must be practical, intelligent, fast, economic, easy to use and understand, futuristic, and almost error free. For example, the airplanes generated a lot of data (about tickets, customers, airports, engine systems, fuel use, crew activity, and even weather systems they encountered). By 2026, annual data generation should reach 98 billion gigabytes, or 98 million terabytes (Forbes June 11, 2017). If we want to present our solution to United Airlines, we need present a working seed project with all the details showing in our running prototype pilot project. Our CRM Metadata is the seed pilot project with analysis, data structure, architect-design, development, testing, management and cost.

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Analysis Data Structure Design-Architect Development Testing Management Cost
Proof of Concept DAO IDAO Resources-STDS Model-STD-Specs Plans-Activities Budgets
Business Plan BO-Managers Structure Factories-Adapters Resources Workers-Workflow Cost Analysis
Data Factories-Adapters Tiers-Cloud Engines-Services Testing Plans Iteration-Milestones Cost Monitoring
Databases Front-end Data Flow Proxy-Security Test Cases Paths-Phases Outsourcing
Tables Back-end Security Commons-Exceps Training Change Control  
Fields-Files Security System Performance Utils-Logging QA Project Tracking  
Business Cases Proxy Business Rules Web Services Documentation Documentation  
Risks Web Services Engines-Services Model-Tiers-Cloud   Acceptance Criteria  
Risk Handling   Processes-Managers Source Control      
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