Data Entry Definition Data entry is a broad term used to describe the process of inserting data into a computer or another electronic device. The data can be inserted in a database, an Excel sheet, CRM, cloud, etc. Sometimes data entry involves inserting data from one digital file to another (e.g, from Google Sheets to Microsoft Excel) and sometimes from a physical document to a digital one. The latter is mostly referred to as data digitisation. Data entry is mostly performed manually but machines can be adopted to speed up the process by using automation, voice recognition, character recognition, etc. Data Entry vs Back Office Sometimes the terms data entry and back office are used interchangeably which causes confusion to most people. Back Office includes all tasks that a company needs to do to support the front office operations. Since the back office department has to do a lot of paperwork, the back office employees need to perform several data entry tasks, such as data capture, data transcribing, data tagging, data annotation, etc. To further explain, Data Entry is usually just a part of the back office processes and it exclusively involves data processing tasks. On the other side, Back Office includes but is not limited to data entry only. Back office tasks depend on the department, industry and business model of a company. Main Data Entry Tasks While the most popular data entry task is copying and pasting information from one source to a database, there are also several other more specific tasks that a data entry employee can manage. Data Tagging- The process of tagging adds a short piece of information or description to an item, allowing it to be indexed, searched on a database, browsed in a catalog, classified, etc. If a company has big data to tag, they would usually outsource the data entry process as it can be very time-consuming. Data Annotation- This is the process of selecting the data, framing or highlighting it and then labeling it. It is used to annotate all types of data, such as pictures, audio, sounds, text, etc. Data annotation is usually used to analyse big data with the help of automation and machine learning. The software that use machine learning will recognize the annotations find patterns learn more about the data make predictions and be more accurate in general. Data Capture- This is the process of capturing, recording and collecting data and information to be later used or processed by a machine. Data capture can be performed manually by a data entry employee or automatically by software. Some technologies used for capturing data are Optical Character Recognition (OCR) tools Intelligent Character Recognition (ICR) Optical Mark Reading (OMR). Data capture also makes use of smart cards, barcodes, QR codes, etc, to collect information. Data Transcription When the source of data or information is an audio/video file that needs to be converted to text, the process is referred to as data transcription. As the name suggests, it is the process of transcribing audio and voice files. Another feature of data transcription is adding subtitles or even captions to the videos. Speech recognition or automatic subtitling can also be used to aid data transcription in cases when a fast solution is needed. Yet, machines are not fully able to provide a 100% accurate transcription and they cannot substitute human labour. Data Logging-This is the process of recording and collecting data to be stored for a specific timeframe for later analysis. Data logging is used for discovering trends, recording parameter information, behaviours, activity, etc. It is often used for scientific purposes or as an IT solution for monitoring networks and systems. This process is almost always performed by a machine rather than a human. Data Processing- After the data has been collected, the data can be processed for several purposes. The main reason for processing data is to analyse it and to produce reports. Data processing can also be used for storage, archiving, organisation, classification, etc. Data Cleansing- This process is used to organise and correct information stored in a database, identify duplicates, errors, outdated information, and to delete irrelevant data. Data Cleansing is used as a form of database maintenance and update. Which companies need to perform data entry? Every company needs to do data entry, but whether they have a dedicated employee or department depends on the volume of information that they need to process daily. All companies need to record some types of information. When? Every day during their daily operations. Such as shift times, worked hours, payslips and payroll, invoices, transactions, storing information, and so on. Depending on the industry, some companies need a more focused approach since data entry is a strategically critical task for their business model. For instance, e-commerce businesses and online shops need data entry to insert their products online, tag them, classify them, and so on. They also need data processing for digitising catalogs and prices. Another industry that needs the most data entry is Transports and Logistics because of the big amount of paperwork about invoices, delivery reports, cargo reports, export and import documents, and transport bills. Recently, Software companies are also in need of data entry and data annotation as a result of the development of AI and Machine Learning solutions. The workload for these projects is usually huge and large teams of employees are needed to meet the deadlines. Some other industries include Healthcare (for medical data, patient records, appointments, medical bills), Finance (Financial forms, bank details, transaction documents, digitisation of documents) and Food and Beverage (online menu updates). Should you outsource data entry? Companies choose to outsource data entry tasks because it enables them to process big data in a shorter time, with higher accuracy and without further investment. We Are Fiber Speed, Quality and Low-cost? No need to settle for less: now you can have all three! WeAreFiber uses advanced technology and infrastructure to ensure that your projects are delivered on time and with a 100% accuracy. Our Quality Department, which is divided into two levels (level one in Albania and level 2 in Italy) will closely monitor the data entry campaigns so that the final product will be delivered with a 0 error rate. Our agent's average tested typing speed is 77 WPM. We provide Data Entry solutions to several e-commerce companies, from sectors such as Retail, Sports, Real Estate and Food & Beverage. Read more about our services.
