Everything you need to know about Data Processing
Data processing is a term used to collect, store, and retrieve raw data to produce informative information.
Data processing is vital for companies and organizations that uses computers to store large amounts of data for later use. This can be done by a data analyst who can manipulate and keep the data in the safest way possible.
Mainly the data to be processed is obtained in a raw format, and processing helps make the information easy to comprehend for its users. It will be simplified into documents, charts, and graphs for use.
Let's dig in for more knowledge served in our article down below as follows;
There are many types of data processing depending on what you are working on. Let's look at some of them and how they work;
There are three types of data processing methods;
This is where by all types of data are processed manually by you as a human being. Whether they are calculations or documents to be done, you are performing them without involving any computer or other electronic devices.
Mechanical data processing is the opposite of manual processing because the data to be processed is done by the use of electronics and mechanical devices. It's much easier, given machines are performing the work for you instead, meaning minimum errors.
If you are using an electronic data processor, it means you are getting results that are more accurate and reliable. This process has been made achievable by computer programs for better results.
The data processing cycle is the process whereby raw data is input into the CPU to be processed from its raw form into a useful form that users can easily understand.
We have six stages of data processing you should know, as stated down below;
This is an important first step to have in mind before going any further. Do you have the data you want to be processed? If not, you will have to provide it for the processing to be successful.
Preparation is achieved by confirming the raw data to be processed for mistakes and any other obstacles that could result in an error.
Input is whereby you are supposed to enter your raw data into the computer in order for it to convert into an understandable language using a CRM system.
Processing data is a stage whereby raw data fed to your computer is processed so that information loaded can be understood. This can be done using the computer’s AI algorithm for an accurate result.
Output data is the final result achieved. At this stage, you can view and read the processed data in whichever format you want it to show up. It could be graphs, documents, or videos, among other ways, that prove to be meaningful to you as a user.
Storage is the last stage, whereby your data has gone through those processes, and you have seen the outcome. Now what's remaining is for you to store it permanently for later use.
Data processing is an important part of the business process in Kenya. It carries with it a lot of benefits, such as;
1. Processing Financial Data
Through processing invoices, inventory tracking, and making pricing decisions. It can also be used to process payables and receivables.
2. Processing Customer Data
By processing customers’ orders, keeping track of their contact information, and making customer service decisions. It can also be used to process customer complaints.
3. Processing Employee Data
Through processing employees’ time sheets, tracking and keeping their vacation days, or deciding on employees' benefits. Employee data processing can also be used to process employee performance reviews.
It can be used to process data for statistical analysis, develop new products, or evaluate marketing campaigns' effectiveness. Data processing for research can also be used to process data for clinical trials.
5. Legal purposes
Data processing for legal purposes can be used to process data for court cases, keep track of legal documents, or make litigation decisions. Data processing for lawful purposes can also be used to process data for intellectual property disputes.
Data processing for security can be used to process data for background checks, to keep track of security incidents, or to make decisions about security procedures. It can also be used to process data for fraud detection.
7. Environmental purposes
Data processing for environmental purposes can be used to process data for environmental impact studies, keep track of environmental conditions, or make decisions about environmental policy. It can also be used to process data for environmental compliance.
8. Quality control purposes
Data processing for quality control can be used to process data for product quality assurances, keep track of quality control procedures, make decisions about product recalls, and process data for customer satisfaction surveys.
9. Human resources
Data processing for human resources can be used to process data for employee recruitment, keep track of employee training, or make decisions about employee benefits and performance reviews.
Data processing for marketing can be used to process market research data, track marketing campaigns, make decisions about product placement, and process data for customer loyalty programs.
Data processing is the way to go for all businesses and companies looking for better and perfect results. Data processing is the future, and if you haven't thought about it, it's high time you go for it. To develop an exemplary data processing system, you need to understand the type of data you are dealing with as an analyst working for your organization.
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