Data available on the Web play a determining role in decision-making both in personal and corporate life. Collecting and storing this data in a structured model helps integrate them with other sources and then use the dataset in various applications, such as event detection and sentiment monitoring. Online newspapers are essential sources of information, accessed daily by thousands of people. To facilitate the exploration of this data, this paper presents ENoW -News Data Extractor from the Web. ENoW receives search strings as input and stores in a relational database data extracted from the news as well as their full content. The system was implemented in Python, using Web scraping techniques. The demonstration comprises the three main functionalities of the tool: newspaper registration, project registration and news extraction.