Why? This is a question we subconsciously answer for most things we do: why do we spend hours reviewing email or sitting on conference calls? But if we take time to consciously reflect on the “Why” of our business activities, I predict it would alter our actions and probably predicate a re-
This is the first in a sequence of blogs that looks at how Planning Analytics and Decision Optimization can help organizations go from a plan to the right plan by leveraging optimization throughout the planning process.
Line-of-business (LoB) stakeholders want to know that their analytics investment will help them make better, faster, and smarter decisions, with measurable business results. But for many, measuring success from applying Machine Learning and Decision Optimization is not obvious. Learn the top 3
This is the fourth in a series of blogs on analytics and the cloud. Read our introduction to the series. This blog concerns itself with the rise of open source software and how it is used for a whole host of analytical purposes. However, as will be seen in this blog, there are significant gaps in
Although NoSQL database technology has been around for a long time (before SQL actually), not until the advent of Web 2.0, when companies such as Google and Amazon began using the technology, did NoSQL’s popularity really take off. Market Research Media forecasts NoSQL Market to be $3.4 Billion by
This is the second in a series of blogs on analytics and the cloud. We will consider the rise of the Internet of Things (IoT), analytics used on that data and how the cloud can be utilized to drive value out of instrumenting a very wide range of ‘things’.
Listen to Dr. Hans Schlenker, Offering Manager, IBM Decision Optimization (DOcplexcloud and DOcenter) as he speaks about how you can solve the real-world optimization problems with IBM Decision Optimization on Cloud.
Prescriptive analytics (optimization) is a sophisticated analytics technology. It can deliver great business value by helping decision makers handle the tough trade-offs that arise when limited resources force choices among options. Optimization was traditionally applied by Operations Research
J White Bear is a data scientist and software engineer at IBM. In this podcast, White Bear discusses simultaneous localization and mapping, an ongoing research area in robotics for autonomous vehicles and well-recognized as a nontrivial problem space in both industry and research.
IBM’s community of big data developers continues to grow. As our Big Data Developer meetup program moves into its fifth year, this worldwide community of customers, partners and IBM developers is on the verge of enlisting its 100,000th member—when we published this blog, we counted 99,100.
Seth Dobrin is vice president and CDO, IBM Analytics, platform development, at IBM. In this podcast, Dobrin shares experiences using Apache Spark for data science transformation and some thoughts on a larger vision for data science transformation at scale.