In the connected world of today’s digital economy, apps, IoT devices, vehicles, appliances and servers are generating endless stream of event data. The stream of events describes what is happening over time and offers the opportunity to track and analyze things as they happen.
Dez Blanchfield talks with Data Scientist & author Lillian Pierson about our Fast Track Your Data 2017 event in Munich, sharing general thoughts on the key themes and topics, in particular how organizations can secure their competitive advantage with machine learning.
Smart companies are finding new ways to squeeze more value out of their massive data storehouses. They’re unlocking insights from their data that build new business models, improve customer experiences and outpace competitors. So where do these business-changing insights come from?
Many of today’s top business performers successfully leverage a discipline – data science. Machine learning is one major way to apply data science and with machine learning, the more data we feed in, the better it performs. However, much of the world’s value data cannot be found on the Internet. It
Analyze your way to business success. Learn more about data analytics and visualization from speakers like Marc Altshuller, General Manager, IBM Business Analytics, at Fast Track Your Data - live from Munich or join online June 22, 2017. Register now.
Imagine what you could build if you could leverage all the data that you couldn’t access before? Learn about hybrid data management from speakers like Nancy Hensley, Director, Growth & Strategy, IBM Analytics, at Fast Track Your Data - live from Munich or join online June 22, 2017. Register
Context-aware stream computing helps you become more responsive to emerging opportunities. By using innovative technologies to understand the context of data and analyze data in real time, you can put data to work.
IBM Analytics VP of Marketing Jeff Spicer sits down with Data Scientist and evangelist Dez Blanchfield to recap IBM InterConnect 2017 and give his insights into a few of the announcements from this year's event.
Building a data lake is one of the stepping stones towards data monetization use cases and many other advance revenue generating and competitive edge use cases. What are the building blocks of a “cognitive trusted data lake” enabled by machine learning and data science?