Is There Any Difference Between Data Input And Data Entry?

by | Last updated Jul 19, 2023 | Published on Nov 15, 2021 | Data Entry Services

Businesses generate a substantial amount of data on a daily basis and if this data is not properly managed, it is likely to get lost in the massive rubble of files and paper. Business organizations face many challenges when accurate data is not entered in an organized electronic system. It leads to lost revenue, unnoticed competitive advantage, missed business opportunity, and other issues. These challenges persist if data isn’t usable or easily accessible. Hiring a professional data entry service helps to convert all data into digital format and make it accessible for proper decision making.

Data entry ensures that all data is entered with completeness, consistency and correctness. This helps to extract valuable business insights that help in the growth of the business. Earlier, businesses used pen and paper methods of entering data and now it has shifted to keyword input and entering data into computers. The process of data entry helps with digital storage of vital data, but businesses are often confused about the terms “data entry” and “data input”. Let us understand the difference between these two terms.

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What Is Meant by Data Entry and Data Input?

Data entry refers to entering any kind of data into an electronic medium like computer or any other electronic device. It helps to compile raw data into useful information. Entering data into spreadsheets helps to combine spreadsheets and applications to draw even wider conclusions and actionable data from it. Huge volumes of data are generated every day and for any organization, data that is relevant or expected to continue to be relevant should be digitized and stored in digital format so that it can be processed by computers.

On the other hand, data input refers to data provided to any computer or software program. The process of providing information to the computer allows computers to design and produce an output. For example, the employee code that you type into the computer along with an impression of your thumb is the input your employer’s attendance tracking system uses to record your presence, which becomes the output.

  • When to use which term: Data entry refers to the process of transferring data from manual form to digital form, either with the help of a data entry expert or any other support. The process of data entry has evolved due to the advancements in technology and it helps to read unstructured data and convert it into structured form. But it still requires human intelligence and nuanced understanding to ensure data entry accuracy. Therefore, the final step in data entry ends with a quality check by data entry experts. Data input is the process of providing relevant information to a software program and this can be done by anyone who wants an output. This process could be automated or outsourced to professionals to get better results.
  • Purpose of data entry and data input: Data entry makes data available to computer systems in a manner that helps to understand the data and act on it. This data becomes useful only if it is relevant, and in a computer-readable format. So, the purpose of data entry is to make information available for computers. Data input provides not just a single purpose but the use of the full power of that data. For example, you input date into ATM software to draw cash.
  • The source of data: In data entry, the source of data could be from a piece of paper but it has major relevance in the future. Therefore, it needs to be shifted from its present storage medium to a different medium that makes it easier to retrieve the data. The main source of the data could be from a paper, forms, or other written materials like prescriptions, resume, lists etc. Even though the source of data is different, all of these should be digitally stored, possibly in the cloud.In data input, the source of data need not be different and it does not require changing data from one medium to another. The software asking for an input is already a part of the digital world. The input could be manual or digital. AI is widely used in this field to intake raw data and with data annotations and labelling. This raw data can be understood by the machines.
  • How it is done: In data entry, there are advanced technologies such as Optical Character Reader and Natural Language Processing that help to automate data entry. However, automated systems require the help of humans to ensure accuracy. In data input, it could be manual entry or it could be an automated input from a digital database based on criteria already known to the software.
  • Verification: Since data entry is a manual process, it needs to be cross-checked and verified manually. This helps to eliminate any chances of error. This can be done either with the help of another person who checks the data against the sources, or by assigning two people to compare against each other and identify any errors.In the case of data input, the data input is given on software application that is expected to be smart. For example, the ATM will not accept a non-numeric figure.
  • Tools needed: Data entry needs basic tools for accessing software and requires a keyword and mouse to enter the data. Technically, the data has to reach a destination software and this could be accessed using devices like headphones, tablets etc. It is much easier and quicker to access a software using a keyboard and mouse. Data entry deals with huge volumes of data and the fastest way to reach the software is the most efficient way.

In data input, tools are a little more diverse since the focus is not on keying in large volumes of data in the shortest possible time.

Today, businesses are very busy carrying out their daily business operations and many organizations rely on data entry services to convert paper-based data into its digital format to derive valuable insights. Technological advancements have made data entry outsourcing more accessible to business enterprises, which has a positive impact on their productivity, growth, and bottom line.

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