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
Augmented reality (AR) and augmented intelligence systems such as Watson are breaking data outside the confines of a two-dimensional monitor and putting them into a three-dimensional visualization format. Big Data and Analytics Hub spoke with IBM AR designer Ben Resnick about what’s next for
Watch to learn how to drive faster insights as machine learning accelerates data classification and quality. Featuring Madhu Kochar, VP Analytics Development, IBM and Anantha Narasimhan, Program Director, IBM.
Are you ready for machine learning? 2018 is shaping up to be the year machine learning gains widespread implementation as enterprises prepare for the future of artificial intelligence. Learn how to accelerate your journey with a fast, scalable approach to machine learning that will give your
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
For decades, a company’s database usually had a single job: operating as either an operational — also known as transactional — database or acting as a data warehouse. It was also typically deployed in a single location: on premises. Today, companies not only want more from their databases, but also
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
Spreadsheets remain one of the most popular tools for business professionals today. Unfortunately, while they can be great for personal productivity, they’re ill-suited for large-scale planning, budgeting and forecasting.
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
Machine learning is being used at the heart of next- generation methods for self-driving cars, facial recognition, fraud detection and much more. At IBM, we’re applying machine learning methods to SQL processing so databases can literally learn from experience.
Your business and your data are both unique. For that reason, your enterprise architecture must also be tailored to fit the exact needs of your business. When data is involved, you want choices, not trade offs. And, more importantly, you want your solutions to build upon and complement one another.
Technology trends and growth areas can vary in different parts of the world. In this week's podcast, Keichii Okada, vice president of IBM Tokyo Software & Systems Development Lab, discusses how natural language technology is helping to advance business strategy and healthcare in Japan. He also