Mapreduce Simplified Data Processing on Large Clusters

https://pixabay.com/photos/stock-trading-monitor-business-1863880/

Information inconsistency occurs when like information is kept in different formats in more than one file. When this happens, it is important to match the data between files. Sometimes, files duplicate some data. When information like names and addresses are duplicated, it may lead to a compromise in data integrity.

What Is Data Integrity?

Information integrity occurs when the information in a database are consistent. Every organization relies on data integrity to ensure that they have reliable and authentic information. The information must also be consistent with real-world events.

When an organization has strong data integrity, the data represents real data. For example, it provides accurate information most a patient'south address and phone number after they take moved.

Data Inconsistency Is Caused Past Redundancy

Redundant data is a problem because it can create unreliable information. One person may change the value in one file simply non in some other file. This is a problem for companies that rely on accurate data.

Allow'south say that a hospital has a system for file processing, but several files for one patient are kept separately. If a professional changes the patient's address in one file but not in any others, the patient'due south pecker, or insurance data could be sent to the wrong destination. If you do not have the right phone number on each file, you may observe yourself running into bug regarding which one to phone call.

How to Prevent Information Back-up

Several methods can prevent data redundancy. For one, planning amend structures for databases tin prevent information from being nowadays in several files. In some cases, this is not possible. Normalizing a database is the next step. The procedure involves cleaning upwards the tables in the database.

The goal of preventing information back-up is to ensure that data is in one identify. It is not scattered throughout the database.

Sometimes an organization tries to normalize a database. They may not exist able to clean up all the redundant information. When this happens, one may run into a data bibelot.

Homo Error

Sometimes, the organization needs to footstep in and ensure that employees are trained properly. Data input can exist tricky, and untrained employees may not realize they are adding new data rather than changing old information.

How to Foreclose Data Inconsistency

People arroyo data inconsistency in 2 means. One way to fix the problem is through fundamental semantic storage. This requires a lot of logging and storing rules. It also involves creating a cardinal area for information. The process can be difficult.

You tin also utilize the main reference store approach. This process seeks to centralize the data. This means that there are strict rules nigh where the database stores information. The goal of this approach is to have more control over of import data. It may require more resources than other methods.

Every organization wants its data to be authentic and reliable. From insurance companies to tech companies, organizations all across the country need to know the information they have collected is useful.