*1.3. Paper Organization*

This review paper will be organized as follows: first, in the introduction, we present our motivations and work related to the topic. Then, the concept of using big data in health will be discussed. The second part focuses specifically on the features and sources most commonly used for big data analysis in healthcare. Additionally, instances of the classification of analytics in medicine are provided. Then, in Part 3, an overview of machine learning techniques and their uses in medicine are presented. The big data technology stack in healthcare is presented in Part 4. In Part 5, different technical and organizational challenges in healthcare are discussed and analyzed.In part 6 a Proposed Strategy for Implementing Big Data Analytics in Healthcare is presented.The final part of the paper is the conclusion, where will summarize and draw final insights (Figure 2).

**Figure 1.** Research methodology followed.

**Figure 2.** Topics covered in this article.

## *1.4. Existing Surveys*

There are many studies in the literature that show the potential big data analytics can offer to medical organizations and what type of data can be analyzed. However, very few studies have shown how data analysis technology is performed in the healthcare sector and what the major organizational challenges are that an organization willing to integrate big data into their system may face. Table 1 presents a summary of the key related reviews, including a description of each review's contribution and the topic covered. A comparison of our work to the others is provided at the bottom of the table.


