Data accuracy is a measure of the extent to which data conforms with reality.
Data can never be 100% accurate, but it can be more or less accurate depending on how close it adheres to reality. The closer that data sticks to reality, the higher its accuracy will be.
In other words, data accuracy refers to the degree to which data reflects what really happened in real life during a specific time period.
Data accuracy meaning
Data accuracy is an essential aspect of data quality. It indicates whether data collected for an item are accurate. In a company, data is gathered from several disciplines.
Every business process has a vast collection of complex data that needs to be maintained in a specific manner, otherwise, data accuracy problems occur.
This data that accumulates in the data warehouse must be perfect and appropriate as it is used for several important business decisions.
A company’s planning, forecasting, budgeting, business intelligence, and all such activities are based on the accuracy of the data.
If the data is irrelevant or incorrect, it can disrupt the entire working system of the business.
There are two factors related to data that needs to be taken care of,
- The data entered must be of the right value.
- It must be correctly presented consistently by the expected data standards of the business and its models.
Why does data inaccuracy occur?
Data inaccuracy occurs because of manual data entry, lack of data standardization, and data decay.
Manual data entry
One of the simple reasons for data inaccuracy is a manual data entry system where there are chances of feeding incorrect details by mistake.
There is a splurge of applications and tools in the market that can reduce the chances of such errors from occurring.
Lack of Data standardization
Data inaccuracy happens due to a lack of data standardization. For example,
EU database and other countries of the world follow DD/MM/YY format to write the date. But the US database follows MM/DD/YY format to write the date.
Consider the date 11/12/2020. When it is converted to content, there will be no accuracy. Therefore, it isn’t easy to decide whether it is 11th December or 12th November.
Data decay is yet another reason for having incorrect data. Over time the existing data of a firm can become redundant and hence lead to data decay.
For instance the personal details of the employees such as addresses or phone numbers.
Hence, the firm must ensure that it has a rigorous data team that is very dynamic and keeps a close tab to data accuracy, enhancing the company’s overall growth and performance.
How to check accuracy of data?
It is crucial to check the accuracy of data. Here questions may arise on how to check the accuracy of data.
I am going to give some tips to check your data accuracy.
- Repetitively analyze data: Analyze data by different people. If you use an excel sheet for data entry, it is not easy to do a repeated analysis of data because it integrates the data. Hence it is better to use some high-level languages like python, SAS, etc.
- Check the data with another source: Compare the present data with another source. Sometimes it is impossible to do. If possible, it is the best process to check the data accuracy.
How to improve data accuracy?
Here are some tips to improve data accuracy.
- The company needs to set an objective for data quality. The topmost management of the organization has to initiate to solve the basic problems that are troubling their data accuracy. Also, it has to set realistic objectives for the data entry team.
- Do not pressurize the data entry team. If the data entry team is under pressure, there will be a chance of data entry errors.
- To improve the quality of data, have an accurate data source.
- From time to time, do a data quality audit to find out very common issues like duplicate, incomplete information, etc.
- The company can make use of the Data Quality Assurance Program to ensure that the data collected from various sources are correct and relevant. This implementation will help the firm to record useful data and keep it.
What are the skills that an employee should have for data entry?
You know that the data entry team members play an essential role in having accurate data. Here, I am listing a few crucial skills that the members should have. You need to consider both hard skills and soft skills.
Good concentration power: He should have high concentration while entering the data. We know that the person who does entry should do that work daily and continuously.
He is a person, not a machine, and has many emotions. So there will be a chance of dropping the focus, and that leads to inaccurate data. Hence select a person who can avoid distractions during data entry.
Trustworthy character: He must be trustworthy. Because many organizations lost their client because of the data stolen. When that person is not trustworthy, he could easily steal the important information of your organization.
Hence while fulfilling the data entry person, check his background thoroughly and ensure he has a trustworthy character.
Experienced with needed software: The person should have the skill to operate the required software. For example, daily, he has to work with many software programs and spreadsheet programs like excel.
The other programs generally used by him are database software, CRM software, and word processor.
So, the candidate should have good knowledge of all the above software and knowledge of computer hardware.
Good typing speed: It is really important to consider the quantity of the data along with quality. Hence the person should have a good typing speed with data accuracy.
You can compromise with the speed but can not compromise with precision.
Good communal skill: The person who does data entry will not work independently. He works with the team. The data will be distributed to the team members to enter or encode within a specified time.
In the case of outsourcing, the amount of data encoded and entered will highly affect the service provider’s revenue.
So the person in the data entry team should regularly communicate with the other team members to ensure that the work is done.
Benefits of accurate and reliable data
Here, we are listing the importance of data accuracy.
- Helps to make a better decision: When data quality and accuracy is high, it allows the users of the organization to get better results, and it also increases the confidence level of workers.
- Increases efficiency: With the help o genuine output, a company can improve its decision-making ability and increase its efficiency.
- Saves money and time: Data accuracy helps to prevent wasting money and wasting time on unprofitable methods, such as sending mail to the wrong address.
- Improves reputation: Good data quality will positively impact your brand productivity, efficiency, and reliability, so that improves your brand reputation.
- Increases productivity: Accurate data allows employees to do the work easily and efficiently by avoiding finding and fixing data errors. Hence employees focus on their target.
- Improves marketing: Good quality of data helps you to market your products or services to the right customers, and also, you can engage customers with your brand, which improves your sales.
- Improves customer satisfaction: Accurate information about your customers helps your marketing team to deliver the products and services at the right time that satisfies your customers.
What is data accuracy?
Data accuracy means data without error that can be used as an authentic source of information to make critical business decisions.
Technically speaking, data accuracy is a measurement that measures “how close the estimate of a parameter from sample data is to its true value”.
Why is data accuracy important?
Data accuracy is important because inaccurate data leads to faulty predictions. If the predicted outcomes are wrong, this leads to wasted time, money and resources.
Accurate data increases the level of confidence to make better decisions, enhances productivity, efficiency & marketing and also helps to reduce costs.
Data accuracy is important for many reasons. For example, if data inaccuracies are found in the results of an experiment, it may lead to false conclusions about the effectiveness or safety of a new drug that could harm people who use it. The more accurate your data set is (with few errors), the better you can understand your findings and make decisions based on them.
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