What Is Data Processing And Analysis Pdf

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Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis.

Acquiring data : Acquisition involves collecting or adding to the data holdings.

Everything about Data Processing | Definition, Methods, Types & Application

Data processing is the conversion of data into usable and desired form. Most of the processing is done by using computers and other data processing devices, and thus done automatically. 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.

These centres houses the critical infrastructure and provide robust processing required to keep services running. 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. 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. 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:. The steps involved in this forms a cycle which resembles data processing cycle and information processing cycle. These cycles might provide instant results or take time depending upon the complexity. 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. 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:. 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.

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. 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.

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.

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. The fundamental of this type of processing is that different jobs of different users are processed in the order received.

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. 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. 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 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.

This method is commonly utilized by remote workstations connected to one big central workstation or server. 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. 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.

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.

Data Processing

Part of the Macmillan Professional Masters book series. Skip to main content Skip to table of contents. Advertisement Hide. This service is more advanced with JavaScript available. Data Processing. Front Matter Pages i-xiii.

Leave a comment. This continuous use and processing of data follow a cycle. With properly processed data, researchers can write scholarly materials and use them for educational purposes. The quality of the final information obtained is directly related to data used in the first place. In principle all surveys run through the same kind of cycle and the typical phases are as follows: 1.

Data analysis is a process of inspecting, cleansing , transforming , and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. EDA focuses on discovering new features in the data while CDA focuses on confirming or falsifying existing hypotheses. Predictive analytics focuses on the application of statistical models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All of the above are varieties of data analysis.

What is Data Analysis? Research | Types | Methods | Techniques

Data processing is the conversion of data into usable and desired form. Most of the processing is done by using computers and other data processing devices, and thus done automatically. 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.

Before you can make use of any structured and unstructured you collect, that data must be processed. The simplest example of data processing is data visualization. For example, most CRM s can spit out data analysis reports in the form of graphs.

Data processing

Data processing is, generally, "the collection and manipulation of items of data to produce meaningful information. The term Data Processing DP has also been used to refer to a department within an organization responsible for the operation of data processing applications.

What is Data Processing?

While data analysis in qualitative research can include statistical procedures, many times analysis becomes an ongoing iterative process where data is continuously collected and analyzed almost simultaneously. Indeed, researchers generally analyze for patterns in observations through the entire data collection phase Savenye, Robinson, The form of the analysis is determined by the specific qualitative approach taken field study, ethnography content analysis, oral history, biography, unobtrusive research and the form of the data field notes, documents, audiotape, videotape. An essential component of ensuring data integrity is the accurate and appropriate analysis of research findings. Improper statistical analyses distort scientific findings, mislead casual readers Shepard, , and may negatively influence the public perception of research. Integrity issues are just as relevant to analysis of non-statistical data as well.

Data processing is the collecting and manipulation of data into the usable and desired form. The manipulation is nothing but processing, which is carried either manually or automatically in a predefined sequence of operations. The next point is converting to the desired form, the collected data is processed and converted to the desired form according to the application requirements, that means converting the data into useful information which could use in the application to perform some task. The Input of the processing is the collection of data from different sources like text file data, excel file data, database, even unstructured data like images, audio clips, video clips, GPRS data, and so on.

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Data Collection, Processing and Analysis