Currently, the blooming growth of social networks such as Facebook, Twitter, Instagram, etc., has generated and is still generating a big amount of data, which can be regarded as a gold mine for business analysts and researchers where several insights that are useful and essential for effective decision making have to be provided. However, multiple problems and challenges affect the decisional ... [Show full abstract] support systems, especially at the level of the Extraction–Transformation–Loading processes. These processes are responsible for the selection, filtering and normalizing of data sources in order to obtain relevant decisions. As far as this research paper is concerned, we aim to focus on adapting the transformation phase with the MapReduce paradigm to process data in a distributed and parallel environment. Subsequently, we set forward a conceptual model of this second phase that is composed of several operations that handle NoSQL structure, which is suitable for Big Data storage. Finally, we implement through Talend for Big Data our new components, which help the designer apply selection, projection and joining operations on the extracted data from social media.