Data lifecycle management (DLM) is a method of managing data across its entire lifespan, from data creation through data deletion. Lifecycle management procedures are automated by DLM solutions. They often arrange data into several layers based on predefined criteria. Based on such parameters, they also automate data movement from one layer to another. Newer data and frequently accessed data are typically kept on quicker and more costly storage media, while less vital data is stored on less expensive, slower media.
Data is divided into phases depending on many criteria, and it progresses through certain stages when it completes various tasks or fulfils particular requirements. A successful DLM process gives structure and organization to a company’s data, which allows critical process goals including data security and data availability.
You might be interested in knowing about the role of data management.
What are the three primary objectives of data lifecycle management?
Organizations are dealing with more data than ever before, and that data may be housed on-premises, in colocation facilities, in edge settings, on cloud platforms, or any combination of these platforms. There has never been a greater need for a successful Data lifecycle management plan, but the strategy must be comprehensive to be effective.
Many resources identify the following three objectives of a good DLM strategy:
Data Confidentiality and Security
Data must be securely maintained at all times to guarantee that private, confidential, and other sensitive information is always secured from potential compromise.
The data must be accurate and dependable regardless of where it is stored, how many people access or interact with it, or how many copies are kept.
Approved users should be able to access data when they need it, without interfering with their workflows or day-to-day operations.
Even Data Management Services ensure the secure and efficient organization, storage, and retrieval of critical business information.
Benefits of Data Lifecycle Management
Data lifecycle management provides numerous significant advantages, including
Data is critical in advancing an organization’s strategic ambitions. DLM aids in the preservation of data quality throughout its lifespan, allowing for process optimization and increased efficiency. An effective data lifecycle management plan guarantees that the data provided to users is correct and dependable, allowing organizations to maximize the value of their data.
A DLM process assigns a monetary value to data at each stage of its lifespan. When data is no longer relevant in production situations, businesses can employ a variety of cost-cutting alternatives such as data backup, replication, and archiving. It can, for example, be relocated to less expensive storage on-premises, in the cloud, or network-connected storage.
Using a data lifecycle management strategy, IT teams may create standards and procedures to guarantee that all metadata is uniformly labeled, improving accessibility when needed. Establishing enforceable governance principles guarantees that data retains its value for as long as it is required to be maintained. The availability of clean, usable data improves the agility and efficiency of business operations.
Compliance and Governance:
Each industrial sector has its data retention requirements and regulations, and a solid DLM plan helps firms stay compliant. DLM enables enterprises to manage data more efficiently and securely while remaining compliant with data protection rules governing personal data and organizational records.
Effective data management is an essential component of developing IT systems that run business applications and provide analytical data to allow corporate executives, business managers, and other end users to drive operational decision-making and strategic planning. We at Intone take a people-first approach to data optimization. We are committed to providing you with the best data integration and management service possible, tailored to your needs and preferences. We offer you:
- Knowledge graph for all data integrations done
- 600+ Data, and Application and device connectors
- A graphical no-code low-code platform.
- Distributed In-memory operations that give 10X speed in data operations.
- Attribute level lineage capturing at every data integration map
- Data encryption at every stage
- Centralized password and connection management
- Real-time, streaming & batch processing of data
- Supports unlimited heterogeneous data source combinations
- Eye-catching monitoring module that gives real-time updates
Contact us to learn more about how we can help you!