The Future of Healthcare and the Transition to Big Data

It’s no secret that trust provides a competitive advantage, with trusted companies outperforming their market peers. Boards, executives, and businesses across the globe want to find ways to build trust with consumers, employees, investors, and all stakeholders. But how do you define metrics, quantify, and measure trust?

The global investment in digital transformation estimated to exceed $10 trillion over the next five years. Despite the tremendous resources going towards this cause, studies show that up to 70% of these initiatives will not achieve their stated goal. What does it take to win?

With the explosive growth of DataOps to drive faster and more confident business decisions, proactively understanding the quality and health of your data is more important than ever. Data observability is an emerging discipline within data quality used to expose anomalies in data by continuously monitoring and testing data using artificial intelligence and machine learning to trigger alerts when issues are discovered.

If you are looking for the scalability and performance needed to support interactive, ad hoc analytics on billions of rows – and with SQL – this latest Data Science Central webinar will show you how to combine distributed, columnar storage and parallel query processing with powerful aggregate functions to deliver faster time to insight using modern, on-demand analytics, as well as how to leverage the power of Kafka and Spark connectors to plug into existing data pipelines. We will discuss the architectural overview of columnar databases, share real-world use cases and give a live demonstration.