In this paper we carried out research on heart disease from data analytics point of view. Prediction of heart disease is a very recanted as the data is becoming available. Other researchers have approached it with deferent techniques and methods. We used data analytics to detect and predict disease's patients. Starting with a pre-processing phase, where we selected the most relevant features by the correlation matrix, then we applied three data analytics techniques (neural networks, SVM and KNN) on data sets of different sizes, in order to study the accuracy

and stability of each of them. Found neural networks are easier to conjure and obtain much good results (accuracy of 93%).

Water separates our planet from all those we are aware of. While the worldwide supply of available freshwater is more than sufficient to meet all of our water demands, the spatial and temporal distributions of that supply are not. There are many regions where our freshwater resources are inadequate to meet domestic, economic development and environmental needs. In such regions, the lack of adequate clean water to meet human drinking water and sanitation needs is indeed a constraint on human health and productivity and hence on economic development as well as on the maintenance of a clean environment and healthy ecosystems. All of us involved in research must find ways to remove these constraints. We face multiple challenges in doing that, especially given a changing and uncertain future climate, and a rapidly growing population that is driving increased social and economic development, globalization, and urbanization. How best to meet these challenges requires research in all aspects of water management This paper identifies the issues facing water managers today and future research needed to better inform those who strive to create a more sustainable and desirable water future.