With each passing day, the world is becoming more dependent on data; every organization must know the answer to “What are the three main goals of data lifecycle management (DLM)?”
Otherwise, it would be tough to compete with the other businesses that are enriched on data. Because the more organized and maintained where data is, the more you will have a leading-edge over others.
And when it comes to managing the data in the best way possible, nothing can be the best possible answer other than the data lifecycle management. That’s why you must have complete knowledge about the DLM and the three main goals of data lifecycle management (DLM). But before heading to details, let us first know in short what data lifecycle management is?
To simply put, data lifecycle management is the method of managing the data flow in an information system right from the data creation to its complete destruction, where each phase consists of several tasks and is regulated by various rules. Continue reading to know further in detail.
What are the Three Main Goals of Data Lifecycle Management (DLM)?
Organizing and managing the data is a tough job, and with each day, the amount of data gets increased with making these jobs more challenging. In fact, you will be surprised to know that the number 1 difficulties that organizations face are the lack of security. As in most cases, while collecting and increasing the information, there are data breaches.
We know how crucial data can be for an organization. It is so powerful that it even has the power to either take an entire origination to its peak or success or breaks it completely.
It is where the data lifecycle management can play a vital role by handling and maintaining the data effectively throughout its lifecycle. In fact, the main goals of the DLM are the basis via which data flow in a liberated and simplified manner.
Although the necessity and requirement of data lifecycle management differ from organization to organization, it has 3 main goals to achieve at all costs. Hence, without further wait, let’s see with a brief explanation what the 3 main goals of data lifecycle management (DLM) are so that you get a complete idea about it:
1. Data Maintenance and Secrecy
With each passage of time, the need, amount, and use of data are getting increased manifold. That’s why the data is given the entitlement of “modern money.” In other words, the more organized and secure your data are, the more you are bound to get success leaving the others behind.
But with the increase in the amount of data, the harder it becomes to maintain and the higher its confidentiality gets prone to risk. The data are so powerful that it can crash an organization’s entire system if it gets into the wrong hands.
For these reasons, the number 1 leading factor that the organization must take into account is how to manage data most securely and effectively possible. Hence what to do so that no data loss occurs and is also managed correctly?
Well, this is where data lifecycle management has played its magic and turned the tables for the invaders. Why?
It has the power to beautifully organize and secure the data in such a way that no data loss, stealing, corruption, viruses occurs. How is it made possible? It has made its rules so strict that no outside people can even access it, let alone thinking of affecting it.
Here, all the structured and well-organized data are stored in the database and in the cloud-based server. On the other hand, the unstructured data are kept in a file or on the cloud server.
That’s why the number 1 main goal of data lifecycle management (DLM) is none other than data maintenance and secrecy. As without it, no data can be appropriately used, and even if used, there will be no protection.
2. Ease of Access
Now that your data is maintained and secured properly, so what is the next thing that you will want? Easy accessibility, right?
No matter how managed and secured data is, if the accessibility is poor, nobody will want to use that data. As in this fast-paced world, we like to use those things that are quickly and easily accessible, not those that have slow and hard availability.
Moreover, when the required data is not found and cannot be used at time of need? The result will undoubtedly be a complete disaster. Why? Because many other processes are directly dependent on the data from the previous process, which is halting their functionalities. What can be worse than such a horrific nightmare?
No wonder that’s why the second main goal of data lifecycle management is the ease of access. With the help of DLM, the accessibility of the data becomes much easier and faster. That one feels enjoy and gets the required data whenever needed at any time.
So the next factor that an organization needs to consider is the ease of use and accessibility of the data. Otherwise, if not taken precaution before, then with time, those organizations will lag behind others and will even find it tough to survive and cope with others.
3. Flexibility and Consistency
Along with an increase in volume, the data keeps getting updated and requires alterations at every instant to cope with changing trends. Furthermore, the use of multi-user environments has gained so much fame that it is rare to find any person who hasn’t still used it.
With the number of users getting increased, numerous instances of data are being produced every instant and, at the same time, being used by several users. This kind of happenings can cause the data to be existing in many locations with slight modifications being made. However, these small changes are enough to make a user confused. It has the power to make a user believe that these organizations’ data are not reliable, so better not to use them. Certainly, you will not want such a painful thing to happen to your organization.
Maybe that’s why the 3rd main goal of data lifecycle management (DLM) is to make sure that the data are flexible enough to make any change and reliable to use as the changes get updated immediately at every place.
Now, let’s look at the data lifecycle diagram to get a better understanding:
Data Lifecycle Diagram
A data lifecycle follows 6 steps in its entire lifecycle, starting from its creation to deletion. Let’s look at those steps:
1. Data Capture
The 1st step is the capture of the data. The incoming data can be gained from outside sources or signals from several systems like the Internet of Things (IoT), Machine Learning (ML)systems, etc.
2. Data Maintenance
After capturing the data, the next step is undoubtedly maintaining the data in the most effective way. Meaning the data needs to be processed in such a way that it is operational and functional after deriving it from the source. Otherwise, it will lose its meaning.
3. Data Usage
Once the data is adequately maintained, it is used for several activities, such as alterations, store, decision-making, analysis, etc., depending on one’s need.
4. Data Publication
Here, in this stage, the data can be shared with numerous users but with only those who have the approved right to access it. Any unauthorized access is strictly maintained and denied to safeguard it from any external danger. In most cases, data sharing is often denoted as the data publication outside the organization.
5. Data Archival
Data archival means storing those data in a different location that is considered not required anymore by the organization. It is kept here in case it is needed any further to avoid facing any kind of problem. It is somehow similar to data storage, with the exception that no data maintenance and use can occur here.
6. Data Deletion
It is the last stage of the data lifecycle. Upon seeing the word deletion, you may have guessed that it means destroying the data. Well, you are right.
Here, in this stage, the unnecessary data that are finally considered not needed anymore gets permanently deleted both from the storage and the archival. Meaning it gets totally erased from the system.
Therefore, these are the description of the data lifecycle diagram along with the three main goals of the data lifecycle management (DLM).
In today’s world, data is equivalent to having money. The more enriched your data, the higher chance you have to succeed in the long run, that too, with zero percent doubt.
Even the smallest of the organization have their own data that needs to be adequately managed to run. Otherwise, it would be challenging to survive in this highly competitive digital era.
That’s why the managing of the data has become more and become essential than ever before. Now that you have a thorough understanding regarding what are the three main goals of data lifecycle management (DLM). Therefore, use and implement the data lifecycle management to manage and keep the organization data flow constant most effectively and securely possible.