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Which Of The Following Data Collection Methods Is Generally The Least Flexible?

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Businesses, scientists, and researchers worldwide utilize databases to go along track of information. Databases can be useful for everything from sending a postcard to all of your customers to discovering results in a scientific study.

However, data becomes less valuable when it is not reliable. Data inconsistency is one of the most mutual threats to reliable information. What is data inconsistency, and what problems does it cause?

What Is Information Inconsistency?

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To use data, it has to be recorded in a format that makes it easy to read and rails. Many businesses utilise electronic databases to rail and store large batches of data. Specially for large businesses or extensive studies, the size of the information to rail may be much larger than can fit in ane file or fifty-fifty on one computer.

Data inconsistencies arise when the data that should be in one database ends upwards in multiple files, each with a different version of the same data. The aforementioned entries could be in the database multiple times. In that location may be multiple versions of the same database where one version includes fields that another version is missing. The result is a set of data that is not accurate or piece of cake to use.

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Although technology makes data easier to runway, improper use of technology 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. Whatever changes have to be visible to all other collaborators in real-fourth dimension. There also needs to exist a consistent, reliable source of data to enter into the database. It would cause data inconsistencies if different individuals were pulling data from the aforementioned sources. It would also lead to redundant and inconsistent data if one or more than of the individuals working on the databases could not see or keep track of the updates fabricated by others.

For example, suppose that 4 coworkers are creating a database of the customer email addresses for a large business. Some emails come from a sales funnel. Others come from a coupon opt-in, and the residue of the emails come from three dissimilar contests. If one coworker is updating a file that is only saved to his hard bulldoze, the rest of the team will non come across the changes he makes. The terminal database will be missing any email addresses he finds.

If the residual of the employees add to a database stored online where changes are visible in real-time, that's a step in the right management, but what about their data sources? It is possible that some customers signed upward for all three contests. Only using a listing of emails from each contest would issue in some email addresses being listed multiple times. The database needs programming rules to forbid indistinguishable entries.

Whether logistical or technological, the problems that can upshot in data inconsistencies have easy solutions. However, yous accept to be aware of the potential issues and develop a plan that works. For big sets of data that multiple people work on, information technology takes careful planning to remove data inconsistencies from the procedure.

Why Is Information Inconsistency a Problem?

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Hither's a real-life instance of data inconsistency on a much smaller scale. Suppose Jack, Ann, and Sheldon are all working on a group project, and they need to write an essay together. They worked together in the library, and they needed to finish the last folio of the essay over the weekend. Jack typed upwards the original file on his laptop. He emails the file to his project partners as a Word document.

Jack continues editing his Word document after emailing his partners. Ann uploads the information to a Google Physician, 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 some other version of the paper. Both papers have three of the same pages, but the fourth folio is unlike. Now, both of the documents are missing information. The group will have to see again to decide which information from both papers to use.

Data inconsistency is far more than serious in business and science than doing a little extra piece of work on a newspaper. Information inconsistency is a huge problem because people make decisions based on information. Inaccurate data results in poor decision-making. Suppose that a database collects responses in a study on a new medicine. If inconsistencies count i,000 positive results twice, a medicine that does not actually work could become to marketplace. If a visitor uses an inconsistent database to mail catalogs to customers, the company could waste material thousands of dollars sending multiple catalogs to the aforementioned household.

How to Prevent Data Inconsistencies

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In that location is a term in engineering science that says, "garbage in, garbage out." If you put bad data into a database, the database tin but give you bad information in return. One of the simplest ways to prevent information inconsistencies is to build rules into the spreadsheet or other database software that is beingness used to track data.

Information inconsistencies usually result in 1 of two problems: duplicate or missing data. Planning and projection management can prevent missing data. For example, a business tin fix a policy that all employees use the same online software that updates in real-time. This will prevent employees from saving dozens of iterations of the aforementioned database on their own computers. Database rules help identify information inconsistencies and remove them before they influence results and decisions. Manufacture-specific software has highly-sophisticated methods of recognizing duplicates. Fifty-fifty the most bones spreadsheet software can be programmed to observe errors.

Understanding what data inconsistencies are is the key to understanding and preventing them. Every bit 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 diversity of problems resulting from it.

Which Of The Following Data Collection Methods Is Generally The Least Flexible?,

Source: https://www.reference.com/world-view/definition-data-inconsistency-5bc80c9fd30c5f1a?utm_content=params%3Ao%3D740005%26ad%3DdirN%26qo%3DserpIndex

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