How Is Traditional Surveying Data Integrated With Computer Technology?
Businesses, scientists, and researchers worldwide utilise databases to keep rails of information. Databases can exist useful for everything from sending a postcard to all of your customers to discovering results in a scientific study.
Nonetheless, information becomes less valuable when it is not reliable. Data inconsistency is ane of the almost mutual threats to reliable information. What is data inconsistency, and what problems does it cause?
What Is Data Inconsistency?
To use data, it has to exist recorded in a format that makes information technology easy to read and track. Many businesses apply electronic databases to track and store big batches of data. Especially for large businesses or extensive studies, the size of the data to track may be much larger than tin fit in one file or even on one computer.
Data inconsistencies ascend when the information that should exist in one database ends up in multiple files, each with a different version of the same data. The same entries could be in the database multiple times. There may be multiple versions of the same database where one version includes fields that another version is missing. The outcome is a set of data that is not accurate or like shooting fish in a barrel to utilize.
Although applied science makes data easier to track, improper utilise of applied science is often the culprit for data inconsistency. Several people can collaborate to make the same data set, but it is important to brand sure that all of the people edit the same file. Any changes take to be visible to all other collaborators in real-time. In that location also needs to be a consequent, reliable source of data to enter into the database. It would cause information inconsistencies if different individuals were pulling data from the aforementioned sources. Information technology would as well lead to redundant and inconsistent information if ane or more of the individuals working on the databases could not see or keep track of the updates made by others.
For example, suppose that four coworkers are creating a database of the customer electronic mail addresses for a large business organization. Some emails come from a sales funnel. Others come from a coupon opt-in, and the residual of the emails come up from three dissimilar contests. If i coworker is updating a file that is simply saved to his hard drive, the balance of the squad will not see the changes he makes. The concluding database will be missing whatsoever email addresses he finds.
If the residual of the employees add together to a database stored online where changes are visible in existent-time, that'south a step in the right direction, but what well-nigh their data sources? It is possible that some customers signed up for all 3 contests. Simply using a list of emails from each competition would upshot in some electronic mail addresses being listed multiple times. The database needs programming rules to prevent duplicate entries.
Whether logistical or technological, the problems that can consequence in data inconsistencies have easy solutions. Even so, y'all have to be enlightened of the potential bug and develop a programme that works. For large sets of data that multiple people work on, information technology takes careful planning to remove data inconsistencies from the process.
Why Is Data Inconsistency a Trouble?
Here'southward a real-life case of information inconsistency on a much smaller scale. Suppose Jack, Ann, and Sheldon are all working on a group projection, and they need to write an essay together. They worked together in the library, and they needed to cease the last page of the essay over the weekend. Jack typed upward the original file on his laptop. He emails the file to his project partners as a Word document.
Jack continues editing his Word certificate afterward emailing his partners. Ann uploads the information to a Google Md, which she and Sheldon edit in real-time. At the end of the weekend, there were two different papers. Jack has one version of the paper that he worked on. Ann and Sheldon have another version of the newspaper. Both papers accept iii of the aforementioned pages, only the fourth page is dissimilar. At present, both of the documents are missing data. The group will accept to come across again to decide which data from both papers to use.
Data inconsistency is far more than serious in business and science than doing a niggling extra work on a paper. Data inconsistency is a huge problem because people make decisions based on data. Inaccurate data results in poor controlling. Suppose that a database collects responses in a study on a new medicine. If inconsistencies count 1,000 positive results twice, a medicine that does non really piece of work could go to market. If a company uses an inconsistent database to mail service catalogs to customers, the company could waste product thousands of dollars sending multiple catalogs to the same household.
How to Prevent Data Inconsistencies
There is a term in technology that says, "garbage in, garbage out." If you put bad information into a database, the database tin can only give y'all bad information in render. I of the simplest means to forbid data inconsistencies is to build rules into the spreadsheet or other database software that is existence used to track data.
Data inconsistencies commonly result in one of ii problems: indistinguishable or missing data. Planning and project management can foreclose missing data. For case, a business can set a policy that all employees use the aforementioned online software that updates in real-fourth dimension. This volition preclude employees from saving dozens of iterations of the same database on their own computers. Database rules help identify data inconsistencies and remove them before they influence results and decisions. Industry-specific software has highly-sophisticated methods of recognizing duplicates. Even the nearly basic spreadsheet software can exist programmed to discover errors.
Understanding what data inconsistencies are is the central to understanding and preventing them. As the maxim goes, an ounce of prevention is worth a pound of cure. It is much easier to fix the causes of data inconsistency than to improve the wide multifariousness of problems resulting from it.
How Is Traditional Surveying Data Integrated With Computer Technology?,
Source: https://www.reference.com/world-view/definition-data-inconsistency-5bc80c9fd30c5f1a?utm_content=params%3Ao%3D740005%26ad%3DdirN%26qo%3DserpIndex
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