In a recent CrowdChat discussion, a group of Hadoop and Spark subject matter experts from the IBM Analytics group discussed using cloud-based Hadoop and Spark services as a lever for business agility. From their contributions we drew ten hot topics and themes for experts in all areas of the big
Some organizations misunderstand the optimized way to use Hadoop and Spark together, primarily because of their complexity. But investing in both technologies enables a broad set of big data analytics and application development use cases. See what Niru Anisetti and Rohan Vaidyanathan have to say
IBM has identified a number of common problems that many businesses find themselves facing in their various stages of Apache Hadoop and Apache Spark adoption. As a result, IBM has developed a set of support services to help customers accelerate time-to-value outcomes and reduce risk when building
Caregivers.com is changing the way senior care providers operate through powerful insights generated through the company’s mobile app. Justin Saul, Senior Director of Technology, Caregivers.com, explains, "with IBM Cloudant and the IBM Watson Data Platform, we were able to quickly iterate on
Without question, our lives are very different from only a couple decades ago, thanks in part to some pretty amazing technology advances including smartphones and other devices, mobile apps, an ever-growing array of social channels and more. Take a look at how one telecommunications organization
At the core of many big data architectures is Apache Hadoop and Apache Spark. Organizations adopting these technologies for their big data journey are nevertheless at different levels of maturity. Hear what Prasad Pandit had to say in an interview with Andrea Braida about how IBM is evolving its
One thing that a recent event in Beijing, China confirmed is there’s no shortage of interest in machine learning for developers in that region. Take a look at snapshots of event highlights featuring rich content on artificial intelligence, cognitive capabilities, machine learning and more presented
Emerging technologies—3D printing, cloud computing, the Internet of Things, mobile computing, sensors, wearable devices and the like—are transforming the ways in which modern organizations manage and use data. But much of that data remains unused. Successfully capitalizing on information
Many forward-thinking organizations want to investigate how big data analytics helps them outthink and outperform the competition. However, many also are challenged with finding the right talent to run the operations, keep the data secure and figure out how to leverage the myriad tools at their
The Internet of Things continues to be a land of opportunity in so many areas. Take a look at this overview of steps to innovation and success factors along with the risks and pitfalls to avoid in your Internet of Things journey.
Nick Pentreath of the Spark Technology Center teamed up with Jean-François Puget of IBM Analytics to deliver the main talk of the Spark & Machine Learning Meetup in Brussels, "Creating an end-to-end Recommender System with Apache Spark and Elasticsearch."
At the recent Spark & Machine Learning Meetup in Brussels, Holden Karau of the Spark Technology Center delivered a lightning talk called "A very brief introduction to extending Spark ML for custom models."
At the Spark & Machine Learning Meetup in Brussels on October 27, 2016, Pierre Borckmans of Real Impact Analytics delivered a lightning talk called "Writing Spark applications, the easy way: How to focus on your data pipelines and forget about the rest."