What Is Data Accuracy?
Defining the accuracy of data begins by knowing what the words "data" and "accuracy" indicate. Data is a set of facts (words, numbers, observations, measurements, etc.) that have been transformed into a type that can be processed by computers. This concept is most applicable to details of past events held on digital media that can be retrieved by computers and used for commercial benefit by business users.
On the other hand, for data to be "accurate," it must fulfill two criteria: content and form. The author Jack Olson writes in his book “Data Quality: The Consistency Factor,” “Form is essential because it excludes ambiguities about the content.” In other terms, the historical occurrence is accurately captured by the content.
For example, think how dates maintained in various formats can be troublesome. 18 November 2018 can be put in the common U.S. format “11/18/2018.” However, there are different writing date conventions, such as 18/11/2018. It might be difficult if someone in the U.S. tried to use the date in that format. As Olson states, "A value if the user cannot tell what it is, is not accurate."
The second condition is that the content of the data needs to be consistent. Consider the instance of "Obstetrics-Gynecology" the specialty of medicine that also known as "OB GYNE," "OB-GYN," "OBGYN" or a variety of other methods. With right but inconsistent values, city names may also be described. "New York City" could, for example, be captured as "New York," "NYC," or "NY." If values for a certain data point are different, it prohibits data from being grouped and summarized by analysts. But since too much data processing requires aggregation, to allow specific data usage, consistent values are necessary. Data accuracy may be described in a nutshell as consistent and correct data contained in digital properties intended for commercial use. Let's dive deeper into the meaning of data accuracy with this understanding in mind. Since information is so valuable, data accuracy is critical for the success of your company. The better the quality, the greater the potential to prosper. Here are five fantastic reasons why your organization cares significantly about high-quality data.
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- Accuracy of Data Makes Greater Decision Making
The best value of data gives everyone who relies on the data a certain degree of trust. If data quality is good, better outputs would be able to be generated by users. This increases the productivity of the company and reduces the risk in the results. Businesses can strengthen their entire decision-making process with accurate results to effectively mitigate any challenges along the way.
- Accuracy of Data Leads to Low Budgets
For any company, data errors are incredibly expensive, but the risk is much greater than just losing revenue. Bad data quality would adversely impact your brand reputation, productivity, and performance in addition to wasting your capital resources. In the worst-case situation, the credibility of your product will be damaged, and you will lose much of your clients. The main thing with bad data is that other mistakes are caused by one mistake, and it takes a considerable amount of time to find and correct these mistakes. You'll have to waste your time correcting mistakes, which is an expensive process, instead of using the newly collected data to create market plans. The failure to deal with the current marketing patterns, without fantastic business prospects, often results in bad data. Losing track of those cycles provides your opponents an edge over you.
- Improved Productivity
The significance of data accuracy goes well beyond just planning. It's related directly to productivity. Data accuracy makes the work of the team even simpler. Your workers will turn their attention to more critical activities and targets instead of spending time on identifying and correcting data errors.
- Aids in Compliance
It is of the utmost significance for every company to adopt multiple regulations, since this directly affects your interaction with consumers. Holding the best quality data, however, makes a big difference between paying incredibly costly penalties and compliance. Regulations keep changing, and with them, the organization has to grow. Maintaining data accuracy, is the only way to achieve compliance.
- Improved Marketing
For marketing campaigns, nothing matters more than data accuracy, so that's why it is not possible to undermine the value of data accuracy. High-quality information makes it easier for you to sell to the right customer, reducing both cost and time. Sending the correct message to the right audience in response means maximizing marketing and revenue. Target marketing produces valued results and helps you expand your business, but most importantly, it enables you to keep your consumers involved with your product.
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A Prerequisite for Artificial Intelligence Is Data Accuracy
As organizations adopt strategies using Artificial Intelligence (AI), data quality takes on ever more importance. A recent joint MIT/Google report found a dramatic market acceptance of Machine Learning (ML). In the study, according to:
- 48% expect that ML would help make them more successful.
- ML initiatives have been adopted by 60% of respondent firms.
- 50% use ML to better understand their clients.
- 22% say the C-Suite would have the main role for the ML programs of their business.
The advantages these companies hope to benefit from AI and ML are focused on high-quality knowledge. Algorithms that use data to make projections and iteratively improve these methods as more data is obtained are at the heart of AI technologies. After being deployed, AI models require minimal human involvement, which places a premium on accurate data. Although AI continues to learn on its own it does not tell whether incorrect data is being used. This implies that AI models' projections may be incorrect or inaccurate, which could influence consumer relationships, competition and growth in sales. Data accuracy is a must for any organization and for that reason professionals having relevant experience and good qualifications (such as a “Microsoft Data Science certification”) are in high demand, as data accuracy is a key to success.