Today, unstructured information represents more than 90% of the information within organizations. This IDC case study estimates that the digital universe will grow 40 percent per year over the next decade and, by 2020 it will reach an astounding 44ZB or 44 trillion gigabytes.
If the first things that come to mind when you think of AI assistants are the likes of Amazon Alexa or Google Home, it’s time to learn about embodied cognition, AI that can physically interact with its environment. A year ago, IBM researchers did just that and brought Watson services into the
How do you choose and learn a new coding language? In this episode of Making Data Simple, we are joined by YouTuber and IBM Social Strategist, Caleb Curry. With over 5M view of his tutorials on YouTube, Caleb has learned a thing or two about how to teach and learn to program successfully. Discover
Organizations everywhere, from massive governments to the smallest start-ups, are in a race for the best-possible data expertise and tools. To help your team understand the data science journey, IBM created the Data Science for All webcast.
If you’re holding an event for the very first time, what helps you gauge its success? At IBM Analytics University, we turned to social media analytics. Here’s a summary of what we learned from the experts and from Watson Analytics for Social Media.
In any successful modern organization, analytics is likely to play a central role in helping decision-makers design and execute effective business strategies. At IBM, as we work with clients across the globe, we’re seeing ever-increasing levels of maturity and confidence in data-driven business
Data, insights, cloud, agile, analytics. These are all terms that get thrown around a lot in technology these days. But the truth is that unless you can combine some or all of these concepts, the bottom line benefit to your business will likely not as great as you may expect.
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.
For today’s data scientists and data engineers, the data lake is a concept that is both intriguing and often misunderstood. While there are many good resources about data lakes on ibm.com and other websites, there is also a lot of hype and spin. As a result, it can be difficult to get a clear
There is a growing need for versatile, hybrid architectures that can combine the best of both data warehousing and big data analytics. The cloud is the perfect solution, because it makes it easier to build a robust data warehouse as a central “hub”, and then add other environments that can be