The panel discusses the challenges and opportunities of Big Data, highlighting the need to address controversies and myths surrounding it. Big Data is not just about size but involves multiple steps in the data analysis pipeline, including data acquisition, information extraction, and analysis. Challenges include defining filters to retain useful information, generating metadata, and handling erroneous data. Effective analysis requires automated processing, compatible systems, and clear data structures. The panel aims to explore whether Big Data is the same as scalable analytics, where problems lie in applications or systems, and if cloud-based platforms are essential. It also considers the role of the data management community in the Big Data ecosystem. The panel includes experts from academia and industry, discussing the importance of collaboration and the need for integrated solutions. The panelists emphasize that Big Data challenges are multifaceted and require interdisciplinary approaches. The discussion highlights the complexity of Big Data, including issues like heterogeneity, incompleteness, scale, and privacy. The pipeline is not linear but involves loops between steps. The panel aims to identify key challenges and opportunities for research and development in Big Data.The panel discusses the challenges and opportunities of Big Data, highlighting the need to address controversies and myths surrounding it. Big Data is not just about size but involves multiple steps in the data analysis pipeline, including data acquisition, information extraction, and analysis. Challenges include defining filters to retain useful information, generating metadata, and handling erroneous data. Effective analysis requires automated processing, compatible systems, and clear data structures. The panel aims to explore whether Big Data is the same as scalable analytics, where problems lie in applications or systems, and if cloud-based platforms are essential. It also considers the role of the data management community in the Big Data ecosystem. The panel includes experts from academia and industry, discussing the importance of collaboration and the need for integrated solutions. The panelists emphasize that Big Data challenges are multifaceted and require interdisciplinary approaches. The discussion highlights the complexity of Big Data, including issues like heterogeneity, incompleteness, scale, and privacy. The pipeline is not linear but involves loops between steps. The panel aims to identify key challenges and opportunities for research and development in Big Data.