Data Quality Management – Data Life Cycle
Every company’s future is linked to data. All business sectors should consider data as a whole in their strategy. New Big Data technologies or connected objects (IOT) do not consider data separately from each other, but as a whole.
Technology and user behavior are changing rapidly, and data collected a year ago is no longer valid. In order to maintain a high level of data integrity, the life cycle of each piece of data and its influence on the inherent quality must be taken into account.
Definition and management of the data life cycle
We can compare the life cycle of a data to the life cycle of any living being.
In fact, we should consider data as a living being. It goes through different stages from the moment it is created, collected, recorded in a system, defined and used, grown by merging it with other data, cleaned and finally deleted. All these steps make up the data life cycle.
What is Data Life Management?
Now that we understand the concept of data’s life cycle, we need to think about how it will be organized within the company and how it will lead to long-term data sustainability.
Each company will offer different organizational structures to support this management, depending on their activity and purpose.
There are 5 major steps in every MLD:
Managing your data’s lifecycle will allow you to optimize the following processes:
- Limit the use of data :knowing the different stages of your data's life ensures that it is safely stored to prevent possible misuse.
- Increase data availability : knowing the management stages, available formats and storage options for your data makes it much easier to access.
- Increase data integrity : implementing distinct management processes optimizes data quality by avoiding the creation of duplicate or unreliable data.
Using tools to manage and validate the relevance of data is becoming crucial to guarantee the quality and integrity of data.
The success and profitability of a company’s business depends on how well data is managed and processed at each stage of its life cycle. Optimizing data management is a demanding task, which requires a daily organization that Data Enso can help you with.
We can be your partner to make your data reliable by implementing one of our Data Quality Management solutions.
Our data validation, verification and enrichment solutions can be quickly and easily integrated into your data collection tools with little development.
You can also use our online solutions to process your data already stored in batch mode.