Whatever your preferred form of analytics, interface preferences, coding skills, or architecture – cloud, on-premises or hybrid - handling more data more simply is in easy reach. In this session, we will explore, with examples from multiple industries, 3 simple steps data scientists, analysts and their teams can take to run powerful, scalable real-time analytics that reduce compute costs, data complexity, and risks. They include:
• simplifying data management and storage processes, including real-time data.
• automating and integrating continuous intelligence that combines new and historical data.
• customizing code and visualization to drive faster, more useful decisions, commensurate with your organization’s bespoke needs and unique culture.