Hard to believe we've arrived at the last day of Think 2018. From keynotes to panels, informal collaborations and learning sessions, we've witnessed first-hand the excitement that conversations about data and analytics bring to business.
Think 2018 is in full swing. We’re inspired hearing from leaders across industries using analytics to transform their business. And we’re thrilled to take part in conversations about data science, machine learning, AI and much more. Here are some highlights from Wednesday at Think.
The excitement, insights and innovation at Think 2018 is truly astounding. Today we heard from IBM Chairman, President and CEO, Ginni Rometty, plus industry leaders and clients who are transforming whole business sectors.
March 16, 2018 is the 25th anniversary of the Db2 relational database product on Linux UNIX and Windows. Over the past 25 years, this team has built the Db2 brand for the distributed product, complementing IBM’s Db2 mainframe offering and creating a market force.
http://www.ibm.com/us-en/marketplace/integrated-analytics-systemHow is data science changing with the availability of high-performance data platforms? Vikram Murali, director of IBM Integrated Analytics Systems and Db2 Event Store development, Jay Wentworth, STSM of appliance architecture, and
In this special podcast, our Making Data Simple Podcast host Al Martin is joined by Caleb Curry, data guru for IBM Hybrid Cloud, and Sam Lightstone, IBM fellow of analytics, to talk about their session at the IBM Think 2018 Conference: "Next-Generation Data Management: Power and Simplicity to the
From machine learning to blockchain to artificial intelligence, data is dominating the conversation in the tech industry. In the first episode of Data Decoded, William McKnight, CEO of McKnight Consulting, and Yves Mulkers, founder of 7wData and a data/business intelligence architect, discuss the
In this week's episode of Making Data Simple, Al Martin and Adam Storm, IBM senior technical staff member and master inventor, next-generation HTAP architect, sit down to talk about fast data. Adam also covers the pros and cons of different information architectures and the software you can use to
While the proliferation of data will be readily apparent, deciding what to do in response will be less straightforward. The majority of workloads currently sit in traditional, on-premises environments but we’ll see many of them move to private and public clouds over the next over the next five
How does artificial intelligence (AI) come into play on a day-to-day basis? In this episode of Making Data Simple, Jean-François Puget, distinguished engineer, machine learning and optimization, and Steve Moore, senior story strategist for Inside Machine Learning on Medium, join host Al Martin to
Join us 27 February at 1 PM ET for "Machine Learning Everywhere: Build Your Ladder to AI." Visit the event landing page to learn more about the event and register for a calendar reminder: ibm.com/mleverywhere
The greatest grandmasters in chess think five moves ahead. In IT, even thinking five moves ahead isn’t enough. A lot of things can happen, planned and unplanned, within the first five moves of an IT strategy deployment that cause a significant amount of disruption both concurrently and long