The data life cycle is a series of processes that occur during the generation, management, and use of data. For example, Walmart collects 2.5 petabytes of unstructured data every hour, akin to a small city’s traffic, as well as the demographics and other attributes of a million customers. For this reason, it is important to understand how and when to organize data. According to the Data Quality Initiative, data can be classified using a multi-temperature scale. Depending on the business process, data can be labeled hot, warm, or cold.
Data can be classified as either hot or cold. Hot data is needed by the organization to perform day-to-day activities. Because of its importance, it must be stored on Tier 1 storage or be optimized for quick access. Cold data, on the other hand, serves no business purpose and is archived or stored for future use. The final stage in the life cycle is called purging, and it involves deleting all copies of data, usually from the archive.
A data’s life cycle includes three phases: collection, active management, and archive. Each stage of the data life cycle is critical and is important for a company’s development and marketing. A successful data life cycle starts with a backup of the data. This copy of the original will be available to the company should a disaster strike. Further, it will be useful for advertising and marketing. Therefore, a company should always have a backup of its data.
After data creation, it needs to undergo a process of data maintenance. This phase can be either manual or automated, and includes data archival. In the first phase, data is created and stored in databases. The next stage is maintenance. This involves cleaning the information before it is ready for use. It can be accessed, used, or archived. The last phase is publication, which makes data accessible outside of the system.
The data life cycle is crucial for a company. It describes the various processes that need to be followed during the lifecycle of data. For instance, data creation includes the collection of valuable information, archiving data, and disposal. The second phase is maintenance. In the case of digital data, the information will be processed, merged, and cleansed before it is finally used. The third phase is disposal. The lifespan of data is measured in days and months, not in weeks and years.
The data life cycle is an important part of any enterprise. While most of the time, it is used for various purposes. The use of data is also a part of the data life cycle. Hence, the term “data management” refers to all the processes that occur during a lifecycle. In the last step, the information is archived. The information is made accessible to the public. It can be used to generate and analyse new products.
The data life cycle refers to the lifecycle of data. The first phase of data creation is the data maintenance phase. It involves storing and transferring information in its database. After it is archived, it is subjected to another process called archiving. Once the data is in the storage phase, it can be used for any purpose. If the information is stored in a database, it can also be used for analytics.
The second stage of data life cycle is the archiving process. This stage is best suited for large organizations that need to store a large volume of data. For this type of data, a DLM strategy is an important consideration. During this stage, the data will be viewed, processed, and archived by authorized users. The next step involves the erasure stage. This is the phase when the information is destroyed.
The third phase is data destruction. In data archiving, the data is deleted and re-used. The lifecycle is defined as the sequence of these steps. The lifecycle is important because it determines how long a data will remain valid. The longer it is kept, the better. The life cycle can determine how much space is needed for the next stage. So, it’s important to ensure the legality of the collected data.
