What is the quality of data quality?

Data quality is a collective term for procedures used to maintain the integrity of data located in different databases. The process of maintaining data quality often requires tasks such as eliminating outdated information, cross references of relevant information found in different databases, and in general they make sure there are no discrepancies with the information found in the database or database set. This type of data cleaning is an ongoing process that is considered a key element of effective data management.

Enterprises of all types are involved in the task of ensuring data quality. Depending on the operating structure of business, this may include the provision of data stored in individual databases, such as sales databases and receivables and liabilities, current and accurate. Other times the process of ensuring the quality of data focuses on the qualifying data before it is stored in a backup, make sure the warehouse data is complete and accurate to the date, when the storage process takes place.

The actual process of ensuring the quality of data often focuses on identifying and repairing any inconsistencies that may be present in data well -kept by enterprise or other organization. This type of data profiling would mean ensuring that similar data in one database was in accordance with the data found in another database. For example, proper data management would dictate that prices extended on a particular customer should be the same in the sales database and in the receivables database. This minimizes the potential of customers who receive inaccurate information regarding their current price structure when talking to the sales department or an accounting department.

In some cases, the Asuranka data quality process involves converting data into a common format, so information can be archived or stored. This is not unusual with data such as payment and receivablesat the end of the year. The harmonization of data before their warehouse provides information with a complete and exact history for previous calendar years that can be accessed at any time and as needed.

One of the side advantages of the quality of data quality is that in the case of a system accident, qualified and archived data that are in storage can be used to partially reconstruct key databases. For example, if it disrupts the company server server, archived data stored on discs or even on the data storage website can be loaded and loaded on a new server. This leaves the task of the reconstruction of any data that has been entered since the last systems were made, instead of reconstructing the months of information from manual records or paying exaggerated amounts of money for attempting to restore data to extract data of the crashed server.