Tips for Businesses to Achieve Accuracy in Data Entry Operations

by | Published on Sep 25, 2020 | Data Entry Services

Data Entry Operations

Data entry is the process of entering data into a database in the required format. Data can be in various formats like sequence of numbers, spreadsheets, handwritten documents, names, addresses, figures or computer codes. When data is entered correctly, the information disseminated would help executives to plan ahead. Inaccurate entry of data can lead to serious problems like poor decision-making, additional errors, inefficiency, and costs. There are many key elements that determine the quality of your business data such as relevance, accuracy, legibility, accessibility, completeness and timeliness. Among these, accuracy is the most important element that determines the quality of data. To ensure professionalism and precision in data entry, businesses can utilize dedicated data entry services.

Modern businesses need smarter business decisions to survive in this competitive world. Thorough analysis and evaluation of data helps with informed decision-making that is vital for the growth of the business. However, data entry operations have some challenges:

    • Managing error rates: The data may be large- or small-volume, but simply copying and pasting data or the drag and drop option has higher chances of error. This is one of the most common challenges that businesses often face. It is important to ensure that you add value to your data by maintaining data quality. You can use various data management tools to ensure that the quality of data is good. Some of the popular data management tools are:
      • SAP Sybase ASE: ASE stands for Adaptive Server Enterprise. This software can perform millions of transactions per second. It allows mobile devices to be synchronized with database using cloud computing.
      • Oracle RDBMS: This is the most popularly used object relational data management software that is secure, occupies less space, minimizes CPU time to process and supports huge databases. It supports Windows, UNIX and Linux versions.
      • IBM DB2: This software is easy to install and data can be accessed easily. It also helps to save huge volumes of data up to petabytes. It is a commercial tool that supports Windows, Linux versions and UNIX.
      • Altibase: This is an enterprise grade, high performance open source data base. It has around 650 enterprises clients including 8 Fortune Global 500 companies. It has a hybrid DBMS with single database that offers high intensity data processing using in-memory database portion and a large storage capacity.
    • Data influx: Data entry is not an easy task, especially if there is a huge volume of data. All businesses cannot afford a team of dedicated professionals to manage data entry. Large volume data can be handled with advanced tools and technologies. This helps business organizations to prevent disruptions caused by inaccuracies of data. Some of the popular big data tools are:
      • Hadoop: This is a popular big data tool that has a huge capacity to process data. This is an open source framework and runs on commodity hardware. It can run on cloud infrastructure. Hadoop consists of four parts known as Hadoop Distributed File System, MapReduce, YARN and Libraries.
      • Apache Spark: This is an open source big data tool that fills the gap of Apache Hadoop concerning data processing. It can manage both batch data and real time data and it processes data much faster than traditional disk processing.
      • Cassandra: This is a distributed type of database that can manage a huge set of data across the server. This is a popular tool that process structured data sets. It offers linear scalable performance, and continuous availability as a data source. It has simple operations and cloud availability.
      • MongoDB: This is a NoSQL cross platform compatible with several in built features. It can store any type of data and offers flexibility in cloud-based infrastructure. It uses dynamic schemas that can prepare data quickly and it also saves cost.

General Electric‘s Flight Efficiency Service recently adopted by Southwest Airlines and used by airlines worldwide, optimizes fuel, safety and much more by analyzing and studying big data. They generate an average of 1000 gigabytes.

  • Quality of data: Most of the time, data quality assurance personnel find a lot of inaccuracies related to complex data fields. Data concerns such as meaningless substitutes, default values and so on prove difficult to analyze if there is large volume data. This affects the quality of data as well as the decision-making process. By simplifying the fields, an organization can reduce the complexity rate of data and thereby minimize the rate of errors.

To overcome challenges such as the above and improve the accuracy of data entry operations, here are some effective tips:

  • Find the source of inaccurate data: Before starting with the data entry processing, knowing the source of inaccuracies of data is vital to ensure that the data is of good quality and reliable. Inaccurate data leads to poor data processing outcome, which is just a waste of time and with poor data processing business organization cannot ensure excellent business intelligence or proper decision-making.
  • Organize your data: Data always comes in an unorganized manner and to make the best use of it, it is vital to convert unorganized data into organized data. Similarly, having an organized team is also important so that the data can be designated to the right person to derive valuable insights from it. Proper data management and data entry processing ensure that the data is well-organized and put to the right use.
  • Develop sustainable solutions: Using the right automation techniques, businesses can build a more sustainable data entry process. With the right communication channels and the proper training, data entry vendors can produce valuable data. They help in contributing positively to the overall sustainability of the process and also maintain the data quality with continuous workflow.
  • Provide better work environment: Data entry is a repetitive task that requires focus and speed. Therefore, having a comfortable working space is essential to maintain the quality of data. Comfortable chairs, proper lighting and ventilation, regular breaks between shifts etc contribute towards ensuring a good work environment and work culture. This helps to improve the efficiency and productivity of the employees.work environment
  • Use advanced software tools and resources: Several software tools and resources are available to make data processing easier. Today, we can even make customized software and resources that meet our requirements. This helps to minimize workload and review the data to ensure delivery of quality data.

All the above-mentioned techniques help to improve data entry operations. The data entered into the system represents business objectives or information. Accurate, factual and reliable data entry is vital to obtain in-depth data insight and actionable data. To avoid expenses related to recruiting, training and maintaining in-house data entry staff, organizations can outsource their data entry operations to professional data entry companies. Data entry outsourcing would enable businesses to focus on core business concerns, and thus improve productivity and revenue.

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