Top Trends in Modern Data Architecture for 2019

Join us for a focused discussion on Data Analytics with health system data analytics leaders. We discuss the decisions, benefits and challenges organizations face when determining how to structure and manage data assets, tools and teams. We’re excited to share diverse perspectives and answer audience questions.

A great comfort with cloud deployment has emerged. Businesses are migrating databases to the cloud or building databases there as a result of scale challenges with the on-premises model, the cloud becoming the “center of gravity”, on-premises databases reaching capacity or emerging uses cases that are specific to the cloud. But not all organizations! And some struggle mightily with the move!Learn about the factors that impact organizations when shifting data and applications to the cloud. What must you consider as you move significant applications and data to the cloud? This webinar will cover the major decision points that management needs to consider when moving to the cloud. These include changes to the software model, development and quality assurance, recovery outage, and disaster recovery as well as new concerns about query performance and service levels, data interchange in the cloud, safe harbor and cross-border restrictions, and security and privacy.

75% of organisations believe they are not living up to their analytics potential. Research has shown that there are 5 major factors holding organisations back from fully utilising analytics in their business, these include: It’s time to change your experience with data and analytics. Data is growing exponentially and and more organisations are starting to realise that becoming data-driven is imperative to their success. Join us for this webinar as we take you through how to transform your analytics capability through data and AI to become a truly data-driven business.

Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. Where are organizations heading in 2019? How are analytic and data warehouse architectures evolving to enable faster and deeper self-service analytics and BI for organizations looking to create a competitive edge? How is public, private and hybrid clouds factoring into deployment decisions? What are the hottest open source projects from Apache Spark to Kudu, Kafka, Hadoop, and beyond?