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One of the main challenges faced by companies involves adequately managing the information at hand, which is essential when making the right decisions. 

Data Lifecycle Management (DLM) allows us to manage the flow of data throughout the entire process that it undergoes from the first touchpoint to the last.

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What is Data Lifecycle Management (DLM)? 

Data Lifecycle Management refers to the definition and structuring of the steps followed by information within a company with the purpose of optimizing its useful life. 

This data management requires the use of resources offered by information technology for its automated processing. Through them, it is possible to collect the data to be analyzed and track it until the moment of its storage or purging.

Benefits of Data Lifecycle Management for companies 

Companies that apply data lifecycle management and ensure good handling of the information that they generate in their everyday operations have several advantages, which include:

  • An adequate data lifecycle management strategy allows for requirements implemented by each industrial sector for data storage to be met.
  • It guarantees a good data protection infrastructure, which helps toward their safety in case of risk or emergency. This applies both to in-house information and customer data that the company works with.
  • The extraction and maintenance of information throughout the data lifecycle allows updated values to always be available.
  • Availability of clean, useful, precise data that is available to all users. This increases the agility and efficiency of company processes.

→ Don't miss this: How to manage product information easily in big companies

Phases of Data Lifecycle Management you should know 

In order to truly understand what the implementation of data lifecycle management implies for a company, it is necessary to know each of the phases that data goes through during its lifecycle.

1. Data collection

The data lifecycle starts with the collection of information. This allows for the creation of values that do not yet exist, but that are necessary as part of a company’s operations. This can be achieved in 3 ways:

  • By purchasing data generated externally
  • By creating data within a company, whether by means of devices or human operators
  • Through the reception of signals, whether in control or information systems, such as the Internet of things.

2. Data maintenance

Once the company has the data, it needs to keep it clean. In other words, to process it so that business processes can continue effectively. This implies actions such as integration, purging or enrichment.

→ The TOP solution for controlling, storing & updating your product information is called PIM

3. Data synthesis

This phase of the data life cycle is not common to all processed information, but is important in cases in which it is necessary to create valuable data through inductive reasoning. This type of analysis is also used in risk modeling, accounting and for investment decisions.  

4. Data use

This phase of the data life cycle is characterized by the application of data collected and processed as part of the company administration. It is necessary to keep in mind that in many companies this information is even part of their business model.

Furthermore, one must also point out that adequately management data in this phase implies knowing the potential use restrictions that may apply to this information.

5.  Data publication

The use of information may also be performed outside the business environment itself. In other words, through the publication of data or its submission off-site.

6. Data storage

Storage is the first step to perform at the beginning of the end of the data life cycle. 

In this phase, data is stored without any further processing, awaiting its deletion from active production environments or its restoration, if necessary.

7. Data purging

Once data is no longer useful in any way to the company, it is purged or deleted from the records. It is essential for this process to be performed correctly to guarantee good data management.

→ This might interest you: Why product information is key in sales impact and ROI

Giving importance to good data lifecycle management and following all of the phases of the data lifecycle is essential to a great number of actions undertaken by a company daily.

Having information management software currently on the market to guarantee the performance of these processes is an important step toward guaranteeing a good data processing in any business. Try our 30-day free demo and take a step towards efficiency.

 

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