Data processing vs Information Processing

What is the difference between Data Processing and Information Processing?
Ans.: Data Processing : Data Processing is a process that converts data into information or knowledge. The processing is usually assumed to be automated and running on a computer. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems to emphasize their practicality. Nevertheless, both terms are roughly synonymous, performing similar conversions; data-processing systems typically manipulate raw data into information, and likewise information systems typically take raw data as input to produce information as output.
Data processing is that a business has collected numerous data concerning an aspect of its operations and that this multitude of data must be presented in meaningful, easy-to-access presentations for the managers who must then use that information to increase revenue or to decrease cost. That conversion and presentation of data as information is typically performed by a data-processing application.
Information Processing : Information processing is the change or processing of information in any manner detectable by an observer.
Information processing may more specifically be defined in terms by Claude E. Shannon as the conversion of latent information into manifest information. Latent and manifest information is defined through the terms of equivocation, remaining uncertainty, what value the sender has actually chosen, dissipation uncertainty of the sender, what the receiver has actually received and transformation saved effort of questioning - equivocation minus dissipation.
Practical Information Processing can be described as a cycle, where data which may have no inherent meaning to the observer is converted into information, which does have meaning to the observer.

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System and its types
Types of System
Types of Information System
Information and its Charcteristics
Level of Business Activity
Information System
Value of Information
Data processing vs Information Processing
Data Collection Methods
Types of Information System
Sub System of MIS
Management Information System
Computerized MIS
Organizational Need for MIS
Factors Responsible for Development of MIS
Effective MIS
Decision Making
Decision Support System
Hebert Simon Model
MIS Planning
Development of MIS
Approaches in Development of MIS
System Analysis
System Analysis and design
Feasibility and Cost- Benefit Analysis
Steps in System Implementation
Evaluation of MIS
Pitfalls in MIS Development
System Documentation
MIS for Finance Marketing Production HRM
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