What do you mean by Data Processing?
Data processing is the conversion of data into usable and desired form. This conversion or “processing” is carried out using a predefined sequence of operations either manually or automatically. Most of the processing is done by using computers and other data processing devices, and thus done automatically. The output or “processed” data can be obtained in various forms. Example of these forms include image, graph, table, vector file, audio, charts or any other desired format. The form obtained depends on the software or method used. When done itself it is referred to as automatic data processing. Data centers are the key component as it enables processing, storage, access, sharing and analysis of data.
More and more information can be sorted in this manner. This help in getting a clearer view of matter and have a better understanding of it. This can lead to better productivity and more profits for the various business fields. The advancement in areas such as data security, machine leaning, data science, network security etc requires a focused approach for reliable, accurate & cost effective processing. All the businesses, especially those which require real time processing need reliable & efficient data center. These centres houses the critical infrastructure and provide robust processing required to keep services running.
What type of data needs to be processed
Data in any form and of any type requires processing most of the time. It can be categorised as personal information, financial transactions, tax credits, banking details, computational, imagery and simply almost anything you can think of. The quantum of processing required will depend on the specialised processing which the data requires. Subsequently it will depend on the output that you require. With the increase in demand and the requirement for such services, a competitive market for data services has emerged.
There are various data processing services available which performs audit, processing operations for a company or organisation collecting data. These services or businesses help other business to comply with the applicable law, follow standard contractual clauses, make data processing agreement, create security documentation, prevent personal data breach and even act as supervisory authority for government.
Applications of Data Processing
- Commercial Data Processing: Commercial data processing involves a large volume of input data, relatively few computational operations, and a large volume of output. For example, an insurance company needs to keep records on tens or hundreds of thousands of policies, print and mail bills, and receive and post payments.
- Data Analysis: In a science or engineering field, the terms data processing and information systems are considered too broad, and the more specialized term data analysis is typically used. Data analysis makes use of specialized and highly accurate algorithms and statistical calculations that are less often observed in the typical general business environment.
- Real World Applications: With the implementation of proper security algorithms and protocols, it can be ensured that the inputs and the processed information is safe and stored securely without unauthorized access or changes. With properly processed data, researchers can write scholarly materials and use them for educational purposes. The same can be applied for evaluation of economic and such areas and factors. Healthcare industry retrieves information quickly of information and even save lives. Apart from that, illness details and records of treatment techniques can make it less time-consuming for finding solutions and help in reducing the suffering of the patients.
- Almost all fields: It is impossible to think of any area which is untouched by data processing or its use. Let it be agriculture, manufacturing or service industry, meteorological department, urban planning, transportation systems, banking and educational institutions. It is required at all places with varied level of complexity.
Why is data processing gaining popularity?
Processing of data is becoming a popular topic because of the various new laws and uses associated with the data. Big companies and MNCs are collecting data by various means which comprises of personal information, customer data, health information, contact information, location data etc. Due to collection of this data, there is an increasing concern over how it is collected and how it will be used. Collecting, storing and processing the sensitive information such as income, medical records, spatial information etc is becoming a concern worldwide. New laws are being framed to regulate what data is collected and how it is processed and keeping in mind the user privacy.
Related Article: Definitions | General Data Protection Regulation (GDPR)
Stages and process of Data Processing
Processing of data is required by any activity which requires its collection. This data collected needs to be stored, sorted, processed, analyze and presented. This complete process can be divided into 6 simple primary stages which are:
- presentation and conclusions
Video explaining Data Processing and Data Processing Cycle
Understanding how data is processed and reading about data processing cycle can often be confusion. This short video on data processing and data processing cycle will help you gain more clarity on the topic. It explains briefly about the data processing followed by data processing cycle.
Different types of output files obtained as “processed” data
- Plain text file – These constitute the simplest form of processed data. Most of these files are user readable and easy to comprehend. Very negligible or no further processing is required in these type of files. These are exported as notepad or WordPad files.
- Table/ spreadsheet – This file format is most suitable for numeric data. Having digits in rows and columns allows the user to perform various operations. For ex, filtering & sorting in ascending/descending order to make it easy to understand and use. Various mathematical operations can be applied when using this file output.
- Charts & Graphs – Option to get the output in the form of charts and graphs is handy and now forms standard features in most of the software. This option is beneficial when dealing with numerical values reflecting trends and growth/decline. There are ample charts and graphs are available to match diverse requirements. At times there exists situation when there is a need to have a user-defined option. In case no inbuilt chart or graph is available then the option to create own charts, i.e., custom charts/graphs come handy.
- Maps/Vector or image file – When dealing with spatial data the option to export the processed data into maps, vector and image files is of great use. Having the information on maps is of particular use for urban planners who work on different types of maps. Image files are obtained when dealing with graphics and do not constitute any human readable input.
- Other formats/ raw files – These are the software specific file formats which can be used and processed by specialized software. These output files may not be a complete product and require further processing. Thus there will need to perform steps multiple times.
Methods of Data Processing
There are number of methods and types of data processing. Based on the data processing system and the requirement of the project, suitable data processing methods can be used. Generally, Organizations employ computer systems to carry out a series of operations on the data to present, interpret, or to obtain information. The process includes activities like data entry, summary, calculation, storage, etc. A useful and informative output is presented in various appropriate forms such as diagrams, reports, graphics, etc. Data processing is mainly important in business and scientific operations. Business data is repeatedly processed, and usually needs large volumes of output. Scientific data requires numerous computations and usually needs fast-generating outputs. Three methods of data processing have been presented below:
Manual Data Processing
Data is processed manually without using any machine or tool to get the required results. In manual data processing, all the calculations and logical operations are performed manually on the data. Similarly, data is transferred manually from one place to another. This method of data processing is very slow, and errors may also occur in the output. Mostly, Data is processed manually in many small business firms as well as government offices & institutions. In an educational institute, for example, marks sheets, fee receipts, and other financial calculations (or transactions) are performed by hand.
This method is avoided as far as possible because of the very high probability of error, labour intensive and very time-consuming. This type of data processing forms the very primitive stage when technology was not available, or it was not affordable. With the advancement of technology, the dependency on manual methods has drastically decreased. This also makes processing expensive and requires large manpower depending on the data required to be processed. Example includes selling of commodity on shop.
Mechanical Data Processing
In this method, data is processed by using different devices like typewriters, mechanical printers or other mechanical devices. This method of data processing is faster and more accurate than manual data processing. These are faster than the manual mode but still forms the early stages of data processing. With invention and evolution of more complex machines with better computing power this type of processing also started fading away. Examination boards and printing press use mechanical data processing devices frequently. Any device which facilitates data processing can be considered under this category. The output from this method is still very limited.
Electronic Data Processing
This is a modern technique to process data. The data is processed through a computer; Data and set of instructions are given to the computer as input, and the computer automatically processes the data according to the given set of instructions. The computer is also known as Electronic Data Processing Machine. Electronic Data Processing is the fastest and best available method with highest reliability and accuracy. Technology used is the latest as this method uses computers. Manpower required is minimal. Processing can be done through various programs and predefined set of rules. Processing of large amount of data with high accuracy is almost impossible which makes it best among the available types of data processing. For example, in a computerized education environment results of students are prepared through a computer; in banks, accounts of customers are maintained (or processed) through computers, etc.
Types of Data Processing
There are number of methods and techniques which can be adopted for processing of data depending upon the requirements, time availability, software and hardware capability of the technology being used for data processing. There are number of types of data processing methods.
This is one of the widely used type of data processing which is also known as Serial/Sequential, Tacked/Queued offline processing. The fundamental of this type of processing is that different jobs of different users are processed in the order received. Once the stacking of jobs is complete they are provided/sent for processing while maintaining the same order. This processing of a large volume of data helps in reducing the processing cost thus making it data processing economical. Batch Processing is a method where the information to be organized is sorted into groups to allow for efficient and sequential processing.
Online Processing is a method that utilizes Internet connections and equipment directly attached to a computer. It is used mainly for information recording and research. Real-Time Processing is a technique that can respond almost immediately to various signals to acquire and process information. Distributed Processing is commonly utilized by remote workstations connected to one big central workstation or server. ATMs are good examples of this data processing method. Examples include: Examination, payroll and billing system.
Real time processing
As the name suggests this method is used for carrying out real-time processing. This is required where the results are displayed immediately or in lowest time possible. The data fed to the software is used almost instantaneously for processing purpose. The nature of processing of this type of data processing requires use of internet connection and data is stored/used online. No lag is expected/acceptable in this type and receiving and processing of transaction is carried out simultaneously. This method is costly than batch processing as the hardware and software capabilities are better. Example includes banking system, tickets booking for flights, trains, movie tickets, rental agencies etc. This technique can respond almost immediately to various signals to acquire and process information. These involve high maintenance and upfront cost attributed to very advanced technology and computing power. Time saved is maximum in this case as the output is seen in real time. For example in banking transactions.
This processing method is a part of automatic processing method. This method at times known as direct or random access processing. Under this method the job received by the system is processed at same time of receiving. This can be considered and often mixed with real-time processing. This system features random and rapid input of transaction and user defined/ demanded direct access to databases/content when needed. This is a method that utilizes Internet connections and equipment directly attached to a computer. This allows the data to be stored in one place and being used at an altogether different place. Cloud computing can be considered as an example which uses this type of processing. It is used mainly for information recording and research.
This method is commonly utilized by remote workstations connected to one big central workstation or server. ATMs are good examples of this data processing method. All the end machines run on a fixed software located at a particular place and make use of exactly same information and sets of instruction.
This type of processing perhaps the most widely used types of data processing. It is used almost everywhere and forms the basic of all computing devices relying on processors. Multi processing makes use of CPUs (more than one CPU). The task or sets of operations are divided between CPUs available simultaneously thus increasing efficiency and throughput. The break down of jobs which needs be performed are sent to different CPUs working parallel within the mainframe. The result and benefit of this type of processing is the reduction in time required and increasing the output . Moreover CPUs work independently as they are not dependent on other CPU, failure of one CPU does not result in halting the complete process as the other CPUs continue to work. Examples include processing of data and instructions in computer, laptops, mobile phones etc.
Time based used of CPU is the core of this data processing type. The single CPU is used by multiple users. All users share same CPU but the time allocated to all users might differ. The processing takes place at different intervals for different users as per allocated time. Since multiple users can uses this type it is also referred as multi access system. This is done by providing a terminal for their link to main CPU and the time available is calculated by dividing the CPU time between all the available users as scheduled.
Laws related to data processing & storage
The increasing concern about user privacy and the collection of sensitive information has resulted in new laws and guidelines which must be followed. These laws differ from country to country and governs how the data is processed, shared and used by a company.
Data protection laws are rapidly improving and changing so as to meet the evolving requirements. Security breach, unauthorized disclosure and data theft are another concerns which requires strict rules and standards to be followed by companies dealing with consumer information. Data processing agreements are formulated and followed by the companies so as to keep them compliant with the data processing and data protection law. There’s a lot of different data protection laws in the world today and it can be confusing to keep up with them. Data protection law is a set of laws that govern how and when personal data can be collected, used or shared. In the UK, it’s a legal obligation for organisations to make sure their customers are aware of how they will use their data. The EU has enacted the General Data Protection Regulation (GDPR) which came into effect in May 2018. There are a number of data protection laws that you’ll need to comply with when you’re taking your business online.
When it comes to data protection, you need to make sure that the data on your site is secure. There are some very good encryption technologies available today that will protect your data and allow you to safely store it on your site. “The Data Protection Act 1998 is an Act of the Parliament of the United Kingdom that regulates how organisations can protect and control the processing of personal data. GDPR rules were brought in with the intention of giving people more control over what their data is used for.
Important Tools & Softwares
- Surveying Tools – SURVEY MONKEY, etc. software tools which help us in easily organizing those elaborated surveys to help us gather the relevant content from the right people.
- Statistical Tools –SAS (STATISTICAL ANALYSIS SYSTEM) etc are statistical calculation tools that help in plotting those big graphs and charts to help us study certain relevant pattern and thus do effective comparisons and draw proper conclusions.
- Calculation and Analysis tools – EXCEL and CALC, etc. are those mathematical software tools that help in applying relevant formulas to process the whole data.
- Database Management tools – ACCESS and BASE, etc. are the tools that help us to manage a large volume of data. It would otherwise become too tedious to look after or refer to as and when we require to do so.