Today, many systems may generate huge amounts of data such as system logs, financial transactions, customer profiles, security incidents, and so on. It is encouraged by the advancement of some technologies like IoT, mobile devices, and cloud computing. There are also fields that specifically learn to manage and process a lot of data like data science and machine learning. A set of data can be processed to produce certain results like detecting anomalies, predicting the future, or describing the state of a system. To generate such a result, the typical phases are collecting data, data preparation, visualization, and data analysis or generating results. In collecting data, we have to take some considerations including the location where the data will be stored, the type of stored data, and the retrieval method or how other systems can consume the data. When we want to select a location, we should consider whether the storage is available in the cloud or on-premise infrastructure, ...