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Data Processing.pptx

This document provides an introduction to data processing and how computers can be used as tools for data processing. It discusses the different types of data processing including business, scientific, and real-time data processing. It also outlines various data processing methods such as manual, mechanical, and electronic data processing. The document notes the advantages of using computers for data processing, which include accuracy, speed, reliability, and the ability to process large volumes of data. It concludes by thanking the reader for their time.

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ACHARYA NARENDRA DEVA UNIVERSITY OF AGRICULTURE & TECHNOLOGY KUMARGANJ, AYODHYA PRESENTATION ON:- INTRODUCTION TO DATA PROCESSING & COMPUTER AS A TOOL FOR DATA PROCESSING SUBMITTED TO:- SACHIN SRIVASTAVA SIR DEPARTMENT OF MBA(ABM) SUBMITTED BY:- ANSHUT CHITRANSH I.D. – A-12354/21 MBA(ABM) 1ST SEM
CONTENT : • DATA PROCESSING • TYPES OF DATA PROCESSING • METHODS OF DATA PROCESSING • ADVANTAGE AND DISADVANTAGE OF DATA PROCESSING • COMPUTER AS A TOOL FOR DATA PROCESSING
DATA PROCESSING
DATA PROCESSING: • Collection, manipulation, and processing collected data for the required use is known as data processing. It is a technique normally performed by a computer; the process includes retrieving, transforming, or classification of information. However, the processing of data largely depends on the following:− • The volume of data that need to be processed • The complexity of data processing operations • Capacity and inbuilt technology of respective computer system • Technical skills • Time constraints
TYPES OF DATA PROCESSING
Types of data processing : • BUSINESS DATA PROCESSING • SCIENTIFIC DATA PROCESSING • REAL-TIME DATA PROCESSING
Business Data Processing : • The process of data in the accounting or business management referred as business or administrative data processing. • In this type of data processing, data is usually in the numeric form. It refers to the all the computing functions that occur in an enterprise. • The computer that is oriented towards business data processing will demand for high speed input and output so that conversion of stored data into report format can occur easily.
Scientific Data Processing : • Data processing in scientific and engineering problems is termed as scientific data processing. • Basically, it is the application of computer simulation and other forms of computation to problems in various scientific disciplines. • It is characterized by relatively little input and output but extensive internal computation. • It emphasize on high speed internal processing but may have limited input and output capabilities.
Real-time Data Processing : • There are many types of large applications that may require the real time data processing. In this, the result is presented at the same time when the data enters. • We can easily analyze this type of data processing in the stock market and currency trends. • The technology which is mostly used in real time data processing is stream processing.
METHODS OF DATA PROCESSING
Data Processing Methods : • MANUAL DATA PROCESSING • MECHANICAL DATA PROCESSING • ELECTRONIC DATA PROCESSING
Manual Data Processing : • In this data processing method, data is processed manually. The entire process of data collection, filtering, sorting, calculation and other logical operations are all done with human intervention without the use of any other electronic device or automation software. • It is a low-cost method and requires little to no tools, but produces high errors, high labor costs and lots of time.
Mechanical Data Processing : • Data is processed mechanically through the use of devices and machines. These can include simple devices such as calculators, typewriters, printing press, etc. Simple data processing operations can be achieved with this method. • It has much lesser errors than manual data processing, but the increase of data has made this method more complex and difficult.
Electronic Data Processing : • Data is processed with modern technologies using data processing software and programs. A set of instructions is given to the software to process the data and yield output. • This method is the most expensive but provides the fastest processing speeds with the highest reliability and accuracy of output.
Examples of Data Processing : • Data processing occurs in our daily lives whether we may be aware of it or not. Here are some real-life examples of data processing: • A stock trading software that converts millions of stock data into a simple graph • An e-commerce company uses the search history of customers to recommend similar products • A digital marketing company uses demographic data of people to strategize location-specific campaigns • A self-driving car uses real-time data from sensors to detect if there are pedestrians and other cars on the road
Advantages of Data Processing : • Highly efficient • Time-saving • High speed • Reduces errors
Disadvantages of Data Processing : • Large power consumption • Occupies large memory • The cost of installation is high • Wastage of memory
COMPUTER AS A TOOL FOR DATA PROCESSING : We need a computer for data processing for various reasons: • Business organizations are bigger and more complex with an increased number of day-to-day activities handled by such organizations. • Traditional, manual methods are too slow to handle manual transactions. Hence, unfinished transactions are pushed forward to another time. i.e. there are backlogs. • Extra time and resources needed to clear the backlogs.
• Accuracy of information may not be guaranteed under manual methods. • Information may not be available on time and this may affect decision making and adequate planning. • Traditional storage of data is inefficient especially with a large quantity of information.
Advantages of Computer as a Tool for Data Processing :  Accuracy of information is guaranteed.  A large volume of data can be processed.  Timely output i.e. It operates at a very high speed.  The diligence of the machine is guaranteed.  Reliability of information.  Tedious jobs can be simplified.  Errors are minimized.  It helps to improve customer service.
THANKYOU For your valuable time