IBM Insight at World of Watson 2016 certainly has a lot to offer, and one good place to start is the conference bookstore. Take a look at this overview for surviving the challenge of finding the right title for your technology of choice.
IBM is joining educators from around the globe in their quest to unleash a new generation of data scientists on the world. During the IBM Insight at World of Watson 2016 conference, discover how data science initiatives and offerings are empowering up-and-coming data scientists everywhere.
If simplicity can fundamentally accelerate focused action, then you can significantly boost speed, productivity and effectiveness in your enterprise. Take a look at this overview of key announcements unveiled on the first day of IBM Insight at World of Watson 2016.
A recent CrowdChat covered team data science as the core competency for digital disruption in today’s business environments. Consider these highlights from that discussion as you prepare for your trip to Las Vegas.
Data is widely seen as the new source of competitive advantage, driving smarter decisions and helping enterprises outthink their rivals. But opportunities are often missed. Getting the data needed from multiple underlying systems can take far too long for application developers, business analysts
The combination of Jupyter Notebooks, Apache Hadoop and Apache Spark has become a killer app for data practitioners. It unlocks the ability to explore, visualize and experiment with both structured and unstructured data sets with great ease and efficiency. We spoke recently with Chris Snow at IBM
SparkOscope helps Apache Spark developers take advantage of the job-level information available through the existing Spark Web UI; minimizes source code pollution; and extends the Spark Web UI with a palette of system-level metrics about the server, virtual machine or container related to each
The inability of lines of business to not serve requests because they have to wait for IT provisioning can lead to a proliferation of analytics silos that can cause a loss of control of data. See how the next big stage of analytics with integrated Apache Spark helps organizations understand the
Fintech products and innovative banking business models are creating a disruption upheaval in the global banking industry. Discover how retail banking can redefine business and operating models by offering innovative customer propositions through implementation of a big data–enabled recommendation
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
IBM Insight at World of Watson 2016 offers you opportunities to explore solutions to your most challenging problems, connect with data engineers and data scientists from other organizations and find out what’s new in streaming analytics. And in anticipation of the event, check out this overview to
Attend IBM Insight at World of Watson 2016 to explore the ways in which predictive analytics is helping modern businesses gain and retain the competitive advantage in their industries. To learn more, review these highlights from a CrowdChat in which industry experts discussed the central role of
IBM extended Big SQL, which was formerly exclusive to the IBM Open Platform (IOP), to the Hortonworks Data Platform (HDP) in September 2016. I recently spoke with Berni Schiefer, an IBM fellow in the IBM Analytics group, to learn more about the offering and the ongoing IBM focus on SQL.
Advances in tools and the capability to work with cloud-based data sets are dramatically changing the nature of data science workloads. Take a look at one data scientist’s quest to learn more about performing data science analysis in the cloud.
Nancy Hensley, director of offering management for IBM Analytics speaks with Rob Thomas, vice president of development for analytics, at IBM, on the subject of business transformation, leading to a discussion of the data maturity curve.