The researcher from the Universidad Internacional Iberoamericana (International Iberoamerican University, UNIB), Dr. Yini Airet Miró, collaborates in research that proposes a secure data management life cycle adapted to the government big data ecosystem (GBDE).
The term data is of Latin origin "datum," which means distinct, unstructured, and unprocessed entity. Organizations process data according to their specific needs to obtain important information, such as events, objects, facts, or concepts. On the other hand, big data refers to data that has characteristics such as high volume, velocity, variety, and veracity.
In the digital marketplace, big data has become an elementary active approach for data-driven organizations. The rise of big data is evident in both public and private sectors. It is often referred to as the oil of the 21st century, given its value in driving the success of non-profit organizations, civil society, and government agencies. Data security is an essential part of the big data life cycle, and machine learning-based encryption algorithms are used to safeguard data from breaches and security threats.
Creating an efficient data management environment is key to optimizing the value of data. Currently, there are several data life cycle models that provide a high-level overview of data management phases. However, it has certain limitations that are especially important in the government big data ecosystem.
The drawbacks are related to security, privacy, and adaptability to different contexts within the government sector. In addition, ethical considerations linked to big data must be taken into account, such as bias and potential discrimination. The government's big data ecosystem involves multiple stakeholders and diverse data sources, requiring effective data management to achieve objectives, improve decision-making processes, and ensure transparency and accountability in public administration.
Therefore, the objective of this research has been to design a data management life cycle tailored specifically to the government big data ecosystem to address the challenges and limitations of existing data life cycle models. The ultimate goal is to optimize the value of data, ensure data privacy, and improve organizational performance in the government sector. To this end, the use of the secure data management life cycle (SDMLC) has been proposed as a model for the big data life cycle. This model is applicable and meaningful in various government fields such as education, transportation, health, and production; it is also applicable for open government data, commercial enterprise data, scientific and research facts.
If you want to know more about this fascinating study, click here.
For further research, check the UNIB repository.
The Universidad Internacional Iberoamericana (UNIB) offers various programs of study. If you want to know about them, click here.