Database Management

Database Management

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In my opinion, problems that are created by having too much data outweigh the opportunities. Therefore, much data is referred to data volumes that might not be stored and processed using traditional database systems. In this case, organizations control too much information as it exceeds the current storage and management capabilities (Kaisler, Armour, Espinosa, & Money, 2013). For instance, nations like the U.S have acknowledged that too much information is a problem in various sectors like healthcare.

Firstly, dealing with too much data leads to complexity in the long run. In this case, too much data exists because of several relationships that are either organized or disorganized. Therefore, the disorganized or organized relationships between data entities leads to complexity. Equally, alteration of any data results in a change of entire stored data. To some extents data alteration may not provide a clear idea of what it contains, this eventually creates a new meaning for the users (Fujitsu, 2015). The aspect of complexity prevents effective use of data due to incompatible formats as well the absence of semantic consistency that causes analytical sprawl. Indeed, due to Analytical sprawl, the act of decision making in an organization tends to be poor.

Secondly, there is poor storage, and processing. When an organization has too much data to store, it is always subjected to multiple data storage either physically or electronically. For instance, back up options that consume time during the retrieval process are needed. Numerous storages also endanger data security because it provides access to unauthorized users from various storage sites. Further, when there is too much data to handle, it lowers the efficiency of a system; thus, more time is consumed during information processing and fast decision making may be unrealistic when too much data is handled in a database.

Thirdly, privacy is a challenge when an organization is managing too much data. While linking of data from multiple sources, common privacy is undermined because external users may have access into the information system. Since there are no algorithms that randomize personal data stored in large volumes, hacking is always common endangering privacy of stored information. For instance, in healthcare organizations, the safety of patients’ information is violated by external users when feeding systems like HITCH with too much data from multiple exist.

Fourth, large volume of information emphasizes on the aspect of quantity as opposed to quality. This means that an organization may have access to more data hoping that it will be able to make a better decision but in the real sense, it finds it difficult because more time is taken to retrieve appropriate information. Therefore, large volumes of data reduce the overall performance of an organization because much of the stored data might be irrelevant in making decisions. The stored information can be vague for the intended purpose since the increase in quantity causes a reduction in value of the existing data record.