The rapid development of digital technologies, IoT products and connectivity platforms, social networking applications, video, audio and geolocation services has created opportunities for collecting/accumulating a large amount of data. While in the past corporations used to deal with static, centrally stored data collected from various sources, with the birth of the web and cloud services, cloud computing is rapidly overtaking the traditional in-house system as a reliable, scalable and cost-efective IT solution. The high volumes of structures and unstructured data, stored in a distributed manner, and the wide variety of data sources pose problems related to data/knowledge representation and integration, data querying, business analysis and knowledge discovery. This introductory lecture serves to characterize the relevant aspects of the Big Data Ecosystem with respect to big data characteristics, the components needed for implementing end-to-end big data processing and the need for using semantics for improving the data management, integration, processing, and analytical tasks.