DLM or ILM ?
What is Data lifecycle management (or DLM for short) ? It's about handling data's full lifecycle inside an information system : from their creation to their deletion (or archiving) when they become obsolete.
Data lifecycle management could be defined as the group of processes implemented in order to manage the enterprise's data from their definition to their retrieval ("technical" point of view). For instance, a typical question in DLM would be "When can you archive a particular datum ?".
Information lifecycle management (or ILM for short) is generally defined as the management of data and their metadata from birth to destruction. By information we mean all data collections meeting user needs. This view takes place at the business level and according to the use of the information ("user" point of view). A typical question in ILM would be "Is this information still timely ?".
To know which strategy you should choose, you first have to understand what a datum is and how your company is going to use it.
You can indeed compare a datum to an atomic element that's part of an information which is necessary to a user. The datum is the raw material and the information is the use thereof.
As an example, let's take a customer file :
- the column "addressLine1" contains a datum on a customer
- the data contained in columns "addressLine1" + "city" + "postalCode" + "country" form an information on the customer = their home address
Life of a datum
The events happening during data's lifecycle are multiple and depend on the type of data and on the enterprise's needs. Each intervention during this cycle can represent a risk for the enterprise (data loss, failure to follow the legislation, data inconsistency...). A smart solution of DLM will naturally lower the "data risks".
Here is a presentation of the crucial steps of a datum's lifecycle, in our opinion, and whichever the origin or use of it :
Our solutions in DLM
Data is our main competence. As a result, Data lifecycle management (DLM) is our field of action; at Rever we can and we do pretend to pose as specialists.
Depending on the events linked to data, Rever offers the adequate tools. Indeed, whichever problem our customer encounters, our solutions will solve the problem thanks to our expertise. This we can guarantee.
In the same way that insurance companies offer a wide range of products (family insurance, car insurance, home insurance...) to protect an individual throughout their life and according to the age, situation and risks met by the insured, Rever's solutions will accompany and secure any intervention on data based on context and evolution of the data's lifecycle.