Data Lifecycle Management is a strategy that is becoming popular in
organizations and companies so that data can be managed properly. So for managing data, the Data Lifecycle Management has made goals. So in this article, we will tell you about Data Lifecycle Management and its three main goals so that you can know its concept completely. In this blog we are going to tell you the What Are The Three Main Goals Of Data Lifecycle Management?, so read this full blog to get the complete information.
About Data Lifecycle Management
Data Lifecycle Management is a system of arranging the steps which are followed by information in an organization so that business data can be managed throughout its life. The need for DLM varies among organizations but has three main goals to fulfill.
Three main goals of Data Lifecycle Management
It is not always easy to manage data and thus there are particular goals needed in Data Lifecycle Management. These goals are:
Data Security or Confidentiality
As we all know, there is a large amount of data stored and in use so there is also a high risk of data being misused. Additionally, as data has become the new currency in the digital world so its security is also very important for any organization or an individual. Therefore one of the main goals of Data Lifecycle Management is to ensure data security so that the data can be protected from being accessed by third-party unauthorized users and can also be protected against malware or from being corrupted.
Availability
Data is the most powerful factor in the digital era so its availability is very important when needed. If the data is not available when needed then it will result in cascading failures of various processes which depend on data. Therefore, data availability holds a high priority and is one of the main goals of Data Lifecycle Management.
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Integrity
In day-to-day working recorded data is used and subject to multiple edits and revisions for every instance. Additionally, as data-centric technologies like cloud computing, the Internet of Things, etc are becoming popular and are being executed so with this, computing in multi-user environments has also increased. So, there are various instances of data created and in use as multiple users access the same database at the same time and thus it can lead to differences in versions that are seen and saved by several users. Therefore, it is important to maintain data integrity which means the same data should be visible to all the users and any iteration to the data must be discreetly reflected in all instances. So this is the last goal of Data Lifecycle Management.
Phases of Lifecycle of Data
To meet the goals of DLM, it must follow a series of phases which are as follows:
Data capture is the first phase during which the data is collected from several sources like sensors, IoT, external databases, etc.
Data maintenance is the second phase which contains digital organization, cleansing, and synthesis of entry signals.
Data usage is the third phase in which data is used as a raw material for analyzing and then providing the value which then converts into information.
Data Publication is the phase in which different users are authorized to use the database.
Data archiving is the phase in which both the data is saved that have not been used together and those which need to be archived for future use.
Data Deletion is the phase that consists of deleting duplicate data to prevent the generation of statistical noise or errors.
The final words
So overall, these three goals of Data Lifecycle Management are for the smooth functioning of any organization and thus they are very essential.