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Data Farm Inc.

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Data and Data Centers Integration and Intelligence
This page covers:

       1. Data
       2. Data Centers

This page gives a quick overview of our approach using our Intelligent Data Access Object (IDAO). Our team is willing to work with vendors, companies, teams or individuals to answer questions and concerns.

Our attempt is to change the IT Community's views of data and data centers
Our IDAO is self-contained and does not need nor it creates any XML code or schemas
Our IDAO does not need any involvement or support from outsiders (code or tools)
IDAO is Java based and will interface with any software, platforms, databases and cloud
IDAO can easily be tested

The Shortcomings of Spring, Struts and Hibernate Frameworks and Their Vendors:
Running in Circles?
We are not sure how to convince Java-J2EE and IT participants, gurus, management and vendors that they are running in circles. Also there have not been any serious advancement in development or data. Spring, Struts and Java 2 Enterprise frameworks or other frameworks did not simplify things nor answer the data and modularity issues. They simply added more XML-schema-code to existing ones plus complicated their structures. The data handling and reusability-modularity of code are still the biggest obstacles in development and integration. Not to mention, Big Data, CRM and BI are not making it any easier.

Our Answer to The Data Handling and Reusability-Modularity of Code:
The best analogy of our approach is we human, we started as infants, children, students, and then finally we graduate into productive adults. We moved from being served to being a server. Therefore, data has to graduate from being dumpy-dummy-idle-storage which we have to go to it to retrieve it. It has to be an active component. It must independently perform its services and travel throughout the system. It would be similar to our human cardiovascular system, where the blood circulate and transport nutrients, oxygen to nourish the body. There are different types of blood cells. Red blood cells which deliver oxygen (O2). White blood cells which are essential for good health and protection against illness and disease. The same principles can be applied to data also.

Intelligent Data Access Object (IDAO):
We need to ask these questions:
How to make data intelligent?
What are the cost and time required to make data intelligent?
Can we automate adding intelligence to data?
Intelligence and learning must be ongoing processes, how do we achieve them efficiency and economically?
How do we perform the data conversion without any system interruptions?
What type of tools do we need to create which help with data intelligence conversion?
How would we automate-document-manage-test IDAO?

Intelligence is the ability to make decision and learn as you go. Therefore, we need to combine data and decision-making in one object which we call Intelligent Data Access Object (IDAO). Plus we need to insure that we are doing the right processes in making IDAO. Therefore IDAO must be tested and pass the tests.

We need to create Business Rules and Decision-making code to add intelligence to our IDAO.

Adding Intelligence:
Adding intelligence to Data Access Object (DAO) is combination of pure data (DAO with set() and get() methods) plus Intelligence Building.

What is Intelligence Building?
Intelligence Building is simply the following steps:

Adding steps-code-methods which collect the needed data for processing
Collecting the actual values to be stored in IDAO
Each method checks incoming data with existing data for accuracy and relationships and returns a score based on the dynamic business rules.
Decision-making based on dynamic business rules
The decision-making method will add all the scores and decides on the course of actions.
Statistic Pool
Tracking the success-failure of each method and each data for future IDAO enhancement (learn as you go).

Conceptually, we are turning decision-making into mathematical formulas that use business rules values to choose a course of actions.

Automation is to find a number of patterns to build an editor that will handle the automation with human supervision.

Our Intelligent CRM Metadata Project:

       "Intelligent CRM Metadata"

Our Intelligent CRM Metadata Project helps teams develop homegrown intelligent cloud solutions.
Our CRM Metadata site is designed and documented using our Project Framework and it covers projects details to give the site visitors how we handle our projects. The bottom of each page lists our frameworks project folders:

       Analysis, Data Structure, Design-Architect, Development, Testing, Management and Cost.

Our Intelligent CRM Metadata Project has more Project folders which we can provide to anyone upon request.

Let look at Microsoft Word or MS-WORD. MS-WORD is an editor which is a graphical word processing program that users can type with. Its purpose is to allow users to type and save documents. It has helpful feature-tools to make documents. Anyone can add graphic and colors to the edited documents.

IDAO Editor:
IDAO Editor makes IDAO from database tables, Java DAO, XML files and code or any source of data (PDF, MS Word, excel sheet, text, etc). It has a graphic interface which helps with the making of IDAO. It has parsing features with dynamic business rules in building IDAO. It is intelligent enough to perform data cross-reference, where it catches errors and makes recommendation. It has statistical pools of data, errors and exceptions which can be used in catching error and performs data-cross reference and recommendations. It tracks all its users and operations for audit trial.

Can we build such an editor?
" Rome Wasn't Built in a Day", but we have the blueprint.

Data Conversion Intelligent Editors:
No one would know how tough and complicated a data conversion is until they are in the middle of one. Most existing databases have issues which are built over the years with hardly any documentation and not to mention the database admin or designers are no longer with the company. There also are tables for products which no longer exist. Therefore, building a parser which would perform more than extract, transform and load (ETL) is a very tough task . It has to retrieve all the fields, make sense out them (name, value, type, precision, label, range, etc), group them, validate, authenticate, certify and eliminate redundancies and miscellaneous.

Our answer to such issues is based on the fact that we are starting with a fresh data template (IDAO) base. Such a template would be created with our intelligent editors. Our editors would be using design-database-patterns, intelligent parsers, automated cross-reference, error checkers and the supervision of database admin. Brainstorming these supporting features is critical to the success of these editors. Management, documentation and testing are as critical as the building our intelligent editors.

We are presenting the following editors:

IDAO Conversion Editor:
Automated parsing of any existing databases to build IDAO, tables (index-lookup-hashing) and XML files with manual editing-management to insure data validation and the additions of intelligent processing-handling.
Business Rules Editor:
Dynamic editing of business rules with properties files and database tables to reduce code updates.
Integration Editor:
Managing the integration with documented tracking-tracing-timeline.
Testing Editor:
Building all inclusive testing which would track-trace-document testing processes (stages, plans, tools, ..etc), testing teams (coordination and performance) and cost (with the assumption of outsourcing testing).

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For more information contact:

(847) 606.9999

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