Data Strucure for Easy Access to Minimum
Businesses, scientists, and researchers worldwide employ databases to proceed runway 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 non reliable. Data inconsistency is one of the near mutual threats to reliable data. What is data inconsistency, and what problems does it cause?
What Is Data Inconsistency?
To use data, it has to be recorded in a format that makes information technology piece of cake to read and rail. Many businesses use electronic databases to rail and store large batches of data. Especially for big businesses or extensive studies, the size of the information to rail may exist much larger than tin fit in one file or even on i computer.
Information inconsistencies arise when the data that should be in one database ends up in multiple files, each with a different version of the aforementioned information. The same entries could be in the database multiple times. At that place 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 easy to utilise.
Although applied science makes data easier to track, improper use of technology is oftentimes the culprit for data inconsistency. Several people tin interact to brand the same data set, but it is important to make sure that all of the people edit the aforementioned file. Any changes have to exist visible to all other collaborators in real-time. There besides needs to be a consistent, reliable source of data to enter into the database. It would cause data inconsistencies if dissimilar individuals were pulling data from the aforementioned sources. It would also lead to redundant and inconsistent data if 1 or more of the individuals working on the databases could not come across or continue track of the updates fabricated by others.
For example, suppose that 4 coworkers are creating a database of the customer electronic mail addresses for a large business organisation. Some emails come from a sales funnel. Others come from a coupon opt-in, and the rest of the emails come from three different contests. If one coworker is updating a file that is just saved to his hard drive, the residual of the team will not see the changes he makes. The final database will be missing any email addresses he finds.
If the residue of the employees add together to a database stored online where changes are visible in existent-time, that's a pace in the right direction, but what near their data sources? Information technology is possible that some customers signed up for all three contests. But using a list of emails from each competition would consequence in some email addresses being listed multiple times. The database needs programming rules to prevent duplicate entries.
Whether logistical or technological, the problems that can result in data inconsistencies have easy solutions. However, yous take to be aware of the potential bug and develop a plan that works. For large sets of data that multiple people work on, it takes conscientious planning to remove data inconsistencies from the process.
Why Is Data Inconsistency a Problem?
Here's a existent-life example of information 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 concluding folio 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 document subsequently emailing his partners. Ann uploads the information to a Google Doc, which she and Sheldon edit in existent-time. At the end of the weekend, in that location were ii different papers. Jack has ane version of the paper that he worked on. Ann and Sheldon accept some other version of the newspaper. Both papers have iii of the same pages, but the fourth folio is different. Now, both of the documents are missing information. The group volition have to meet again to decide which information from both papers to use.
Data inconsistency is far more serious in business and science than doing a trivial extra work on a paper. Data inconsistency is a huge trouble considering people make decisions based on information. Inaccurate information results in poor decision-making. 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 not really piece of work could go to market. If a company uses an inconsistent database to mail catalogs to customers, the company could waste product thousands of dollars sending multiple catalogs to the same household.
How to Prevent Information Inconsistencies
There is a term in technology that says, "garbage in, garbage out." If y'all put bad information into a database, the database can only give you bad information in render. One of the simplest means to foreclose data inconsistencies is to build rules into the spreadsheet or other database software that is being used to track information.
Information inconsistencies usually result in one of two bug: duplicate or missing information. Planning and projection management can prevent missing information. For instance, a business can set a policy that all employees use the same online software that updates in real-time. This will preclude employees from saving dozens of iterations of the aforementioned database on their own computers. Database rules assist place data inconsistencies and remove them earlier they influence results and decisions. Industry-specific software has highly-sophisticated methods of recognizing duplicates. Even the near basic spreadsheet software tin be programmed to detect errors.
Agreement what data inconsistencies are is the central to agreement and preventing them. As the saying 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 variety of problems resulting from it.
Source: https://www.reference.com/world-view/definition-data-inconsistency-5bc80c9fd30c5f1a?utm_content=params%3Ao%3D740005%26ad%3DdirN%26qo%3DserpIndex&ueid=a3910e12-157e-4f1d-8ffd-df00f418df4d