VivianKingasia/Tanzania-Water-Wells-Project-Prediction-Analysis

# Tanzania Water Wells Project Prediction Analysis A study by World Bank Group in 2019 showed that 29% of all waterpoints in Tanzania are non functional with 20% of them failing in the first year of installation and 40% failing within 20 years(long-term). This is a major problem for NGOs who invest funds in addressing the clean water crisis in this country. Ensuring access to clean water and functionality of waterpoints are therefore objectives of many NGOs as a form of intervention to address this public health crisis and development challenge. NGOs tasked with contributing towards the Sustainable Development Goals in relation to the water crisis need to understand the physical infrastructure conditions of these water sources, why they fail in order to develop better interventions needed to sustainably address this water crisis. NGOs also need to understand where to direct funds either towards maintaining existing functional water systems and types of technologies to invest in to ensure continued access to clean water. NGOs are our main stakeholders in this predictive analysis. There are some aspects that need to be explored and answered through this project analysis. Through machine learning predictive analysis with data collected by the Tanzanian Ministry of Water and Taarifa(technological company), we will able to predict which water pumps are functional and which are not to determine which need to be maintained or repaired. We will also explore the cost of water consumption for the people of Tanzania (do people pay to access water or not), whether management schemes, waterpoint technology and aspects such as population affect conditions of the waterpoint. This information will inform the role that NGOs as well as what kind of support they need from other stakeholders such as the Tanzanian Government, local communities and private firms to close the gap in water access and help Tanzania meet its 2030 SDG goal of providing universal clean and safe water. In t …