How IT Companies Safely Process Electronic Data

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May 3, 2019

How IT Companies Safely Process Electronic Data

Electronic data is information recorded in a way that requires electronic devices such as computers to interpret, process, and display. On the other hand, electronic data processing is a series of operations on a computer that interprets, manipulate, classify, summarize, and record data. Electronic data processing aims at managing and protecting the integrity of documents. 

As the years unroll, data is turning into an invaluable asset for most businesses and other organizations. Consequently, hackers are targeting data held by various institutions, reaping vast sums of money from ransoms paid by companies whose data is compromised. To shield against attackers, businesses now prefer to entrust IT companies such as Fusion Computing Limited with the roles of safely processing their electronic data.

Elements of electronic data processing

There are four essential components of electronic data processing. They include hardware, software, procedure, and personnel. The hardware consists of the physical and tangible parts of a computer. Hardware is used to record and store data. Computer software is a set of instructions that guide how machines perform given tasks. In the case of data processing, computer software consist of custom applications, databases, spreadsheets, among many other pieces of code. A procedure is an organized set of coded instructions that capture and manipulate electronic data. Procedures are designed to eliminate redundancy and corruption of data. Personnel is the staff trained to operate electronic data processing procedures. 

Stages of electronic data processing

There are four stages of electronic data processing. They include collection, preparation, input, and storage. Sometimes, these stages can be compressed into three, including input, processing, and output. 

The collection stage entails gathering data and is the most crucial step of all. If accurate data is not collected, then all the other phases of data processing will be futile. Customer data is an example of data gathered during the collection stage. 

Once raw data is collected, it is taken through the preparation stage. Preparation entails cleaning and transforming raw data before inputting it in the right format into a computing system. 

The input step entails sending data into a computer using an input device such as a keyboard, digitizer, or scanner. 

After data is collected, prepared, and keyed into a system, it is taken through processing. Processing entails various data manipulation techniques. These operations involve comparing, classifying, sorting, among many other procedures that transform data into information. 

Once data is converted into information via processing, it is ready for transmission to relevant parties who need to use it. The output data is stored in the right format for retrieval or future use by relevant authorities.  

Techniques of electronic data processing

There are eight methods of electronic data processing utilized by most reputable IT companies. They include: 

  • Time-sharing electronic data processing
  • Real-time electronic data  processing
  • Online electronic data processing
  • Multiprocessing
  • Interactive electronic data processing
  • Multitasking electronic data processing
  • Batch electronic data processing
  • Distributed electronic data processing

All of the above are expounded in the subsequent paragraphs. 

Time-sharing electronic data processing

In time-sharing, many terminals are connected to a central processing unit at the same time. However, in actual sense, each terminal is allocated a given time slice in the CPU’s sequence. This means that a user of a given terminal can complete a given task within the time slice assigned to the terminal. If the allocated time elapses before the task is completed, the user has to wait for the next time slice allocated to the terminal. 

Online electronic data  processing

Reservation of airline and train tickets are examples of online data processing scenarios. Suppose you are booking a plane or train, a computer processes your incoming data upon submission. Consequently, it updates the transaction file and makes a reservation. You are then given an immediate response to the events to follow. This type of data processing maximizes on delivering data output for efficient service delivery. For online data processing to occur, the CPU must be directly connected to a data input unit. This is achieved through a communication network. 

Real-time electronic data processing

Automated Heating Ventilation and Cooling Systems (HVAC) serve excellent examples of real-time data processing. Accurate information is collected and manipulated. After which an immediate response that influences the next tract of events is provided. Just like online processing, real-time data processing achieves prompt, efficient service delivery. For example, when the temperature set for a given room is surpassed, an automated HVAC system automatically turns on to restore comfortable temperatures.  

Multiprocessing

Multiprocessing entails processing more than one task at the same time on one computer. Multiprocessing computers contain more than one independent CPU, which operate together in a coordinated manner. Servers are examples of multiprocessing units. 

Interactive electronic data processing

In interactive processing, one action leads to the next. A user inputs data which is manipulated and output displayed. The response presented requests the following input to execute the next out until the desired information is achieved. 

Multitasking electronic data processing

Multitasking involves working with different processors at the same time. Take an example of the banking industry where banks have different branches. These branches have different customer accounts, all of which can be centrally administered from the central server. Hence, the various tasks in different offices share the same processing resource. 

Batch electronic data processing

Batch processing accumulates data over some time. The data is then processed at once when the data collection period elapses. A good example is payroll systems. Employee data is collected in terms of hours worked and their rate per hour for a given time, for instance, one month. The information is consequently used to process payment for the given period. 

Distributed electronic data processing

ATMs serve perfect examples of distributed processing. This type of processing leverages the use of remote workstations for efficient service delivery. All the remote work stations are synchronized with the mega workstation. 

In summa, electronic data processing runs on different modes, all of which target speed and efficiency at which information can be delivered. Additionally, EDP reduces the costs of managing data as well as eliminate duplication of efforts. 

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