Data is the core asset of all organizations. Enabling the use of data across the enterprise and outside the organization has become an imperative. The database management market is undergoing a rapid and profound transition to the cloud, as the supporting technology is changing. Cloud and dbPaaS has become the platform of choice and pricing models are under pressure from both open-source and the cloud.
What is driving the data infrastructure transformation to new technologies, cloud platforms and cost models?
How are existing technologies changing and what new technologies are emerging to support this transformation?
What are the vendors doing to address the shift to the cloud and how will the market evolve?

AI is not the only thing driving rapid change in data and analytics. From the next generation of augmented analytics tools to the use of continuous intelligence to interpret streams of data from IoT or the potential of intuitive interfaces, there is rapid evolution in how and where analysis can be deployed. Understanding the business impact of these changes will allow organizations to prioritize the innovations that will drive digital business.

The new data and analytics platform is the cloud. Cloud service providers and independent software vendors are providing the basis for a new cloud based ecosystem. In this session, we will explore the state of the data and analytics platform (data management, BI/analytics/data science, data and analytics governance), the transition to cloud and its implications, and what it means to operate successfully in the cloud, or more likely, in multiple clouds.

Everyone wants a data lake, but most attempts fail to live up to hype around this concept. This session explores the multiple reasons why data lakes fail and how you can avoid the traps. Specifically, this session covers:
- What are the major scenarios for data lake failures?
- How can you detect and correct these scenarios?