The emergence of massive amount of data in clinical and healthcare fields leads to the need to implement a Big Data Analytics platform in medical area, due to the advantages of scalability and efficiency of these proven architectures and platforms in the processing and management of large datasets. Big Data Analytics is the process of analyzing huge amounts of data from different sources of data and different formats, like electronic health records, prescriptions, medical imaging or genomic data in order to deliver useful information used to take decisions in real time. Software tools and applications for predictive analytics or data mining enable those implied in healthcare industry to improve the quality of clinical services or an early diagnosis of diseases. Big Data Analytics can generate revenues by providing insights for third parties, such as payers (patients, health insurance companies), or pharmaceutical. In the paper we will present issues and how we intend to solve them with an open source platform for clinical Big Data processing. The objective is to facilitate development of more efficient clinical and healthcare applications and improve accuracy of predictions.