**1. Introduction**

The health sector has always generated a large amount of data due to the increased record-keeping needs in the context of patient care [1]. Much of this available and particularly valuable data are in a semi-structured or unstructured form. Further, its diverse and dynamic nature makes it challenging to extract valuable insights through the use of traditional analytical methods [2]. Thus, big data in the field of health is an important issue, not only because of its enormous volume but also because of its diversity and how quickly it can be managed [3]. The human capacity to process this data is limited, making effective decision support necessary. Due to this, big data analytics must be integrated into the health industry. Big data analytics has the capability to examine a diverse set of intricate data and generate valuable information that would otherwise be unobtainable. In the healthcare field, it can not only detect emerging trends but also enhance the quality of healthcare, decrease costs, and facilitate prompt decision-making [4]. As stated in the McKinsey International Institute report, if big data are harnessed and used effectively, the U.S. healthcare system value will be saved more than \$300 billion annually, with approximately two-thirds of that amount coming from a reduction in healthcare costs of around 8%. By making use of big data technology and the automated analysis of the results, it is possible for useful information to emerge that until recently has remained in obscurity. The ability of big data analytics to recognize the heterogeneity of diseases allows not only a timely diagnosis but also for the evaluation of existing treatments [5,6]. Big data analytics can turn large amounts of continuous data into actionable insights by analyzing and connecting

**Citation:** Berros, N.; El Mendili, F.; Filaly, Y.; El Bouzekri El Idrissi, Y. Enhancing Digital Health Services with Big Data Analytics. *Big Data Cogn. Comput.* **2023**, *7*, 64. https:// doi.org/10.3390/bdcc7020064

Academic Editors: Domenico Talia and Fabrizio Marozzo

Received: 13 February 2023 Revised: 9 March 2023 Accepted: 16 March 2023 Published: 30 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

information from multiple sources. This capability to provide this kind of insight is especially crucial, particularly in emergency medical situations, as it can greatly determine the outcome of a patient's life or death [7]. We have seen during the coronavirus pandemic the usefulness of medical data and how such information can be helpful in the managemen<sup>t</sup> of health crises during a pandemic. Health organizations must seriously consider integrating the technological tools required to treat this massive amount of data that has the potential to save lives. The digitization of clinical examinations and medical records in healthcare systems has become a widespread and accepted norm since the development of computer systems and their potential [8].
