The document outlines the stages of data lifecycle management in the USA, starting with data creation and ending with data deletion. Key steps include data storage, processing, distribution, and archiving, each critical for maximizing the value of data in business decision-making. Proper management of the data lifecycle ensures security, efficient storage, and effective use of information.

1. Data Life Cycle Management Services in the USA

2. Stages Of Data Lifecycle Management
• Data Creation - The data lifecycle starts with data collection or creation. Data is
abundantly available everywhere. However, organizations should collect data
based on its quality and importance to their business. Data can be extracted from
mobile and web applications, surveys, forms, etc.
• Data Storage - Once the data is created, storing plays another important role as it
helps to access the data whenever necessary. Data can be stored using different
mediums like computers, external storage devices, or the cloud. Creating a backup
for stored data saves the organization during data deletion, corruption, or malware
attacks.
• Data Processing – For the raw data to be productive, it has to be analyzed,
processed, and refined further. As a part of the data processing workflow, data is
validated, filtered, reformatted, analyzed, and presented as usable information.

3. •Data Distribution - Once the data is analyzed, the next big step is data distribution;
this enables organizations to define who uses the data and to what extent. This is
the most crucial step where data delivers its full business value; it plays a major role
in business decision-making and communication with various stakeholders.
•Data Archive - Data archiving is essential to the data management lifecycle. In fact,
it is the activity during which data is often examined, cleansed, and preserved. This
process guarantees data security by preserving and making information available
for future use. Archived data is, in essence, a gold mine.
•Data Deletion -This is the final phase of DLM, where the data is deleted and
destroyed securely from the records. Too much unrequired data will consume
storage space and become a burden for the business. Hence the data is deleted from
archives too when it exceeds the required retention period.

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