How Data Exchanges Enable Secure Data Collaboration

In a global economy, real-time data analysis is closely related to business success. Without data-driven insights, organizations find it challenging to remain competitive, improve company performance, and deliver strong user experiences, regardless of their industry. To match the pace of business, companies require transparent, data-driven relationships.

Faster Analytics with Cloudera Data Warehouse (CDW) Demo Highlight

The cloud-led journey to digital transformation requires organizations to become significantly more data-driven, yet traditional data warehouses have difficulty with new data volumes, new data types, and a variety of use cases. In this session, we will show you how Cloudera Data Warehouse offers a guide to your cloud journey by offering a modern hybrid cloud solution for an unprecedented scale that delivers insight to every part of your organization, faster while saving costs.

Meeting Medical Device Data Privacy, Governance, and Security Challenges

Medical devices have become increasingly complex as technology evolves, and the sheer number of these devices now being worn or implanted has grown exponentially over the past few years. There are currently over 500,000 different types of smart, connected medical devices in use that have the ability to collect, share, or store private patient data and protected health information (PHI)(1).

Snowflake Helps Finnair Improve Customer Experience with Cloud Data Analytics

Coronavirus has impacted the travel industry, but as it adapts, there is one factor airlines have always worked hard to minimize: delayed flights. Arriving late or missing a connection can severely impact the customer experience, which is why airlines work hard to maintain high rates of on-time performance (OTP). To that end, pilots may have to use extra fuel to make up for a delayed departure or to reach a destination early, even if it means circling the airport before landing.

Predicting 1st-Day Churn in Real-Time - MLOps Live #7 - With Product Madness (an Aristocrat co.)

Michael Leznik - Head of Data Science Matthieu Glotz - Data Scientist Yaron Haviv - CTO & Co-Founder We discuss how technology and new work processes can help the gaming and mobile app industries predict and mitigate 1st-day (or D0) user churn in real time — down to minutes and seconds using modern streaming data architectures such as KAPPA. Also, we explore feature engineering improvements to the RFM (Recency, Frequency, and Monetary) churn prediction framework: The Discrete Wavelet Transform (DWT).