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    Today in the corporate world, most decisions are data-driven. Businesses harness the power of data for every day-to-day task- from new product designs to customer acquisition.

    They obtain data from various sources such as marketing campaigns, customers, emails, cloud mobile apps, and social media- to count a few.

    Since businesses constantly receive different types and volumes of data by leaps and bounds, it is an uphill task for them to manage the heaps of data residing in their systems. 

    This data deluge can work magic when businesses use it to their advantage once they implement the right tools to manage it. 

    One of the most popular solutions business leaders deploy within their organizations is data lifecycle management (DLM). It is a process that involves the management of data throughout its lifecycle that begins from its acquisition and ends in deletion.

    Putting the right DLM strategies in place will help businesses leverage the data whenever they need it. 

    So, let’s shine some light on the three goals of data lifecycle management that can help you get the most out of the data. 

    But, before that, let’s first go over to understand what DLM is:

    What Is Data Lifecycle Management (DLM)?

    Data lifecycle management is defined as a comprehensive approach to managing data in an organization. Whether you call it a process, set of procedures, or policies, its primary objective is to monitor data throughout different stages across databases, systems, applications, and storage media.

    Today, a single piece of data can execute manifold processes, so it is never discarded. Instead, businesses store these bits of data in their systems for years to link them with other pieces and form a big picture. This continuity of data makes DLM a never-ending circle. 

    DLM involves policies that are implemented to manage the flow of information in an organization’s data systems- from data creation to execution and archiving and all that comes in between.

    A well-run and strong data management process ensures that organizations understand, map, and control their data throughout the journey, as it is created, published, modified, and stored. The lifecycle of data management involves the following six stages:

    1. Data acquisition 

    Data enters a system through data entry or when another system sends it.

    1. Data storage and maintenance 

    The data is processed for validation and accuracy and then stored in the relevant system.

    1. Data usage 

    The constructed data is converted into usable formats that a specific software can interpret. 

    1. Data publication 

    Data is sent to the concerned platforms and published for concrete use (for example, purchase orders (data) are printed and attached with the shipments)

    1. Data archiving 

    Once a piece of data is used for its purpose, the system archives it.

    1. Data cleaning 

    If systems find the data no longer in use, they clean it or shift to less costly or on-premises storage systems.

    These stages reflect how a piece of information moves through different systems within an enterprise. 

    Now that you know what DLM is and how it works- read on to understand what benefits it offers you in the shape of its goals.

    What Are The Three Main Goals Of Data Lifecycle Management (DLM)?

    For businesses, managing data is quite tough at times. With DLM, they can monitor and control the flow of information across systems to keep it in usable and accessible formats.

    Data lifecycle management ensures this through underlying goals that form the basis by which it makes data flow streamlined and unhindered. The three goals of DLM are as follows:

    1. Security or Confidentiality of Data

    With a massive volume and miscellaneous types of data out there available for use, the risk of misuse of data is always high.

    Since data is the driving force in the business arena, its security is the foremost concern of organizations and individuals.

    Thus, it becomes crucial to guarantee data security and confidentiality. To achieve this, data lifecycle management incorporates data security best practices as one of its core capabilities to ensure a strong data protection infrastructure. 

     DLM keeps data from being accessed by unauthorized users (such as cybercriminals). It also ensures data protection against being corrupt or malware.

    1. Data Availability

    Data is the building block of various operations in this digital era, so it must be readily available whenever needed. When data is not accessible to the right people when they need it, it results in consecutive failures of multiple processes that depend on each other to obtain data.

    Data availability holds significant importance in data-driven services. Therefore, DLM offers cloud solutions that make it available at a faster rate for customers and employees before they demand it. 

    1. Data Integrity

    With the growing popularity of data-centric technologies, multi-user computing environments are increasing. Multiple users accessing the same database at the same time can lead to various versions of the same data.

    To avoid redundancy and maintain integrity, data lifecycle management consistently updates data. It makes clear and precise data available to all users, accelerating the agility and efficiency of business processes. DLM also prevents information silos which can hinder essential business collaboration. 

    How Does Data Lifecycle Management (DLM) Help Businesses?

    Businesses face massive challenges in terms of managing the vast data volumes they gather and administer. With data lifecycle management, they ensure secure supervision and high-quality maintenance of the data they generate to gain several advantages. 

    Deploying data lifecycle management helps them manage a wide range of miscellaneous data securely to mitigate security risk and control costs that they otherwise need to spend on the installation of huge data storage systems.

    DLM offers them many other benefits such as:

    • Identifying data bottlenecks
    • Improving management of historical data
    • Empowering the ability to conduct a root-cause analysis
    • Facilitating teams easy access to data
    • Moving data to less costly on-premise systems when it is no longer in use


    To Summarize

    Adopting the right tools to manage data is a smart decision that many companies take when they deploy data lifecycle management. DLM improves various areas of businesses and delivers myriad advantages.

    With DLM in place, you not only manage data but also prevent silos, improve data consistency, reliability, and accessibility across your business systems.

    Now, it is time for your business to implement the right DLM strategy and manage the flow of data for all future processes.

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