Tuesday, May 19

Track B: Competing on Analytics

Julie Langenkamp, Director, Editorial & Content Strategy, Radiant Advisors

B101. Becoming an Analytics-Driven Enterprise

10:45 AM2020-05-192020-05-19

Tuesday, May 19: 10:45 a.m. - 11:45 a.m.

Competitive pressure is escalating as more organizations use technology and analytics to identify opportunities and address customers' needs more thoroughly. There are a variety of approaches to enable better decision making and enhance customer experience.

Getting Executive Buy-In for Digital and Analytics Transformation

10:45 a.m. - 11:45 a.m.

Like many other industries, the insurance sector is changing rapidly due to evolving customer expectations and disruption caused by the emergence of non-traditional, tech-savvy new entrants. Arbella engaged its executives to begin the long journey toward a complete transformation of the company. The goal was to become an analytics-driven enterprise, including addressing concerns and overcoming initial resistance. The presentation concludes by showcasing the proof of concept for the initial project.


, Head of Analytics & Data Science, Arbella Insurance Group

, Senior Actuarial Analyst, Arbella Insurance Group

Case Study: How Accelerated Analytics of Massive Data Propelled This Enterprise’s Business

10:45 a.m. - 11:45 a.m.


, CMO, SQream


B102. IoT, Analytics, and Streaming at Scale

12:00 PM2020-05-192020-05-19

Tuesday, May 19: 12:00 p.m. - 12:45 p.m.

According to Cisco, 500 billion devices are expected to be connected to the internet by 2030. Organizations are using new technologies to capitalize on this wealth of IoT data by analyzing it rapidly for timely insights.

IoT Sensor Analytics With Apache Kafka, KSQL, and TensorFlow

12:00 p.m. - 12:45 p.m.

Large numbers of IoT devices are leading to big data and the need for further processing and analysis. Learn how to leverage Kafka and KSQL in an IoT-sensor-analytics scenario for predictive maintenance. A live demo shows how to embed and deploy machine learning models—built with frameworks such as TensorFlow, DeepLearning4J, or H2O—into mission-critical and scalable real-time applications.


, Technology Evangelist, Confluent


B103. Analytics Best Practices Today

02:00 PM2020-05-192020-05-19

Tuesday, May 19: 2:00 p.m. - 2:45 p.m.

The speed and volume of data flowing into organizations is intensifying. but many companies are only able to leverage a relatively small portion of it to better serve customers, identify trends, and improve operations. Implementing best practices is critical to succeeding with data analytics today.

Trials and Tribulations: How to Build and Scale a World-Class Analytics Team

2:00 p.m. - 2:45 p.m.

Want to build a world-class in-house analytics team? MINDBODY is an American SaaS company headquartered in San Luis Obispo, Calif. The company provides cloud-based business management software for the wellness services industry. Learn how its data science department scaled up from a small collection of SQL reporting analysts to a successful, centralized team of data analysts, engineers, and scientists that produces high-quality and heavily adopted analytical models for all areas of its global SaaS company.


B104. Enabling Real-Time Analytics

03:15 PM2020-05-192020-05-19

Tuesday, May 19: 3:15 p.m. - 4:00 p.m.

The ability to quickly act on information to solve problems or create value has long been the goal of many businesses. However, it was not until recently that new technologies emerged to address the speed and scalability requirements of real-time analytics, both technically and cost-effectively.

Building a Real-Time Multi-Tenant Data Processing and Model Inferencing Platform

3:15 p.m. - 4:00 p.m.

Each week, 275 million people shop at Walmart, generating interaction and transaction data. Learn how the company's customer backbone team enables extraction, transformation, and storage of customer data to be served to other teams. At 5 billion events per day, the Kafka Streams cluster processes events from various channels and maintains a uniform identity of each customer.


B105. Succeeding With Data Science in the Real World

04:15 PM2020-05-192020-05-19

Tuesday, May 19: 4:15 p.m. - 5:00 p.m.

There are many considerations that factor into data science success in the real world. Ultimately, success is about the right combination of technology, processes, and people.

You Built It, But They Didn't Come: How to Make Your Data Product Indispensable

4:15 p.m. - 5:00 p.m.

Executives are worried about having an AI strategy. Data scientists worry about getting their models to be as accurate as possible. IoT teams stay busy juggling telemetry, alerts, and APIs. Report developers do their best to visualize the data, and engineers try to glue it all together and ship it. However, if business value is dependent on specific users engaging successfully with a decision support application or data product, then teams must design these solutions around the people using them—not the data or technology. Learn how human-centered design provides a process to help teams discover, define, and fall in love with customer problems.


, Founder & Principal Designer, Designing for Analytics

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