Intelligent CRM Metadata
Our Project Executive Summary Team and Management Goals

Existing Data
Regardless of database vendor and latest technologies, data is stored in logical storage structures, data blocks, segments, tables, fields and files. Both structured and non-structured data are dummy data for other software tools to store or retrieve it as bytes or blocks. Data itself is dummy bits stored into the databases. We can safely assume that data and databases are composed of three layers system:

       Dummy data storage
       Store-retrieval software tools
       Processing software to make data presentable and useable

We can also safely assume that most existing data for businesses are what we described and we are providing an answer to such existence. We are not here to create DNA storage, but we converting existing system without any changes in database hardware or software. We are creating a new format.

Revolutionizing Data
To revolutionize such structure we need to:

Make data intelligent, where data processes itself
Build a way for data to perform all these three layers as an intelligent service
Such a service must be dynamic and has the ability to correct itself
Data should be able to travel through any software system the same way blood travels through our body.
Both storing and retrieving data must fast and easy to use by other software
Data should track itself and keep statistic or reports on its performance

Keeping Data Dynamic
Dynamic Business Rules are nothing but text parameters which can be edited to change the data processes on the run without changing or modifying any code.

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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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