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Discriminate Between Data and Information

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Submitted By mulka
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Meaning and definition of data and information
Data is the raw material for data processing. The data relate to facts, event and transactions. Data refers to unprocessed information. Information is data that has been processed in such a way as to be meaningful to the person who receives it. It is anything that is communicated.
For example, researchers who conduct market research survey might ask a member of the public to complete questionnaires about a product or a service. These completed questionnaires are data; they are processed and analyze in order to prepare a report on the survey. This resulting report is informative. Data | Information | Originated at mid 17th century | Originated in late middle time | Data are raw facts. | Information is processed data | May not always be meaningful. | Information is always meaningful. | Input to any system may be treated as Data

| Output after processing the system is Information | Data must be processed to understand. | The information is already in understandable form, it may be processed further to make it more understandable. | Difficult to Understanding | Easy to Understanding

| Data may not be in the order. | Information should be in the order | Example: Statistics, numbers, characters, images. | Example Reports, Knowledge | Data is used as input to the computer system. | Information is the output of data. | Data is unprocessed facts figures. | Information is processed data. | Data is not specific. | The information is specific | Data is a single unit. | A group of data which carries news are meaning is called the Information. | The data doesn’t carry a meaning | Information must carry a logical meaning. | Data is the raw material. | Information is the product. |

DRM
The DRM is a framework whose primary purpose is to enable information sharing and reuse across the US Government via the standard description and discovery of common data and the promotion of uniform data management practices. The DRM describes artifacts which can be generated from the data architectures of federal government agencies. The DRM provides a flexible and standards-based approach to accomplish its purpose. The scope of the DRM is broad, as it may be applied within a single agency, within a Community of Interest.
Smart Data
According to the definition smart data is as follows
1. It acts like a performance optimizer
2. It is Interoperability technology helps in exchanging and sharing Data
3. It uses Data- aligned methods and algorithms
Smart Data provides solutions, businesses use technology to improve productivity and reduce costs.

DoDAF
The Department of Defense Architecture Framework (DoDAF) is the “overarching, Comprehensive framework and conceptual model enabling the development of architectures [for Agencies within the DoD].” Conceptually this is an EAF-in-practice similar to FEAF, and what I Mean by that is that DoDAF is a framework that was developed for a specific context and client, and was not designed to be used beyond those bounds. In contrast to more abstract frameworks like Gartner, TOGAF and ZF which were designed to solve a general issue with the EA development across a wide array of organizations, DoDAF was designed to solve a wide array of specific issues within a singular organizational context, the Department of Defense (DoD). DoDAF was designed to support six key processes within the DoD: the Joint Capability Integration and Development System; the Defense Acquisition System; Systems Engineering; Planning, Programming, Budgeting, and Execution; Portfolio Management; and Operations. DoDAF ascribes a data-centric approach to serving these processes. The method DoDAF requires is Model-driven, that is specific templates of data that are used to aggregate and communicate data on a specific architectural issue. When these models are complete they become a “View” of a facet of the current DoD architecture. In DoDAF 2.0, there are 8 prescribed Viewpoints:
 All – Architecture contexts which impact all other viewpoints
 Capability – Requirements, Delivery Timing, and Deployed Capabilities
 Data and Information – Data Interrelations, and Alignment
 Operational – Operations Use and Supporting Scenarios
 Project – View of Projects impacting current capabilities and other views
 Services – Relates Performers, Activities, Services, and their interactions
 Standards – Compliance with applicable standards
 Systems – Legacy Support for interconnecting systems
The DoDAF provides a foundational framework for developing and representing architecture descriptions that ensure a common denominator for understanding, comparing, and integrating architectures across organizational, joint, and multinational boundaries. It establishes data element definitions, rules, and relationships and a baseline set of products for the consistent development of systems, integrated, or federated architectures.
1. Very Oriented to Military Operations
2. Still very Applicable to NASA and Other customers
FEAF
The Federal Enterprise Architecture Framework (FEAF), like DoDAF is an EAF-in practice with its enterprise being the Federal Government of the USA. FEAF is one of the most fragmented EAF's and currently spans five documents: a five-part reference model, a methodology, a maturity model, a best-practices guide as well as considerations as to how to have FEAF compliment SOA. The FEAF Reference Model includes the following sub-models:
 Performance Reference Model – Identifies and Standardizes EA output measurements
 Business Reference Model – Aligns the Federal Enterprise Architecture along  Service Component Reference Model – Organizes latent components and services for reuse
 Technical Reference Model – Organizes standards and technologies currently in use
 Data Reference Model – Provides a standard method for the description, categorizing and sharing of information within the Federal Government Functional, not organizational lines.
Enterprise architecture (EA) is a management best practice for aligning business and technology resources to achieve strategic outcomes, improve organizational performance and guide federal agencies to better execute their core mission. An EA describes the current and future state of the agency, and lays out a plan for transitioning from the current state to the desired future state. Federal enterprise architecture is a work in progress to achieve goals.
1. Superset of DoDAF, Zachman, etc.
2. Levels 1.2 and 3 are concerned with Budget, Business Goals, External Drives, Etc
3. Mandated for USG agencies

Bibliography
1. mcsweeney.co.uk
2. appareltechnology.wordpress.com
3. http://en.wikipedia.org/wiki/View_model
4. online.ist.psu.edu

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