Growing demand for data has created a bottleneck. How can organizations satisfy the increasing needs of data users without overburdening their technical teams? Starting with self-service analytics, this session explores why more self-service capabilities — including self-service data preparation, self-service data quality and self-service data integration, are becoming a necessity.

The impact of AI is much wider than some specific use cases or industries. With the increased focus on sustainability, organizations are working on ways to increase their energy efficiency while at the same time minimizing their carbon footprint and costs related to it. AI is one of the enabler for meeting these sustainability goals.

Most data lake failures result from underestimating project resources or omitting required technologies. Organizations underestimate skills, time, data volumes, design requirements, governance and adjusting their traditional experience to the new paradigm of the data lake. This presentation discusses the many requirements of the modern, multiuse data lake, so organizations can avoid failures.