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
Ever hear of the Big Data Dudes? If not, crawl out from under that rock and see what these intrepid big data and analytics heroes are up to in their latest analytics blockbuster, "Big Data Dudes and the Lost in Las Vegas Mystery."
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
To serve citizens effectively and efficiently, public entities can draw from the private sector’s 360-degree view of the customer and apply analytics, big data, Hadoop, machine learning and Spark to create a single or 360-degree view of the citizen. See how this methodology can empower public
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
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
We are excited to announce the GA of the BigInsights for Apache Hadoop Basic plan on Bluemix! Over the last three months, the service has been available as a public beta. It was encouraging to see the participation and feedback during the beta. The feedback has been valuable in improving the
Why has IBM created its own distribution of Apache Hadoop and Apache Spark, and what makes it stand out from the competition? We asked Prasad Pandit, program director, product management, Hadoop and open analytics systems, at IBM to give us a tour of the reference architecture for IBM Open Platform
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
Data science seems to be experiencing a renaissance when it comes to advanced open source tools. Get a glimpse into creative application development with IPython Notebooks, Jupyter Notebooks, Apache Spark, the PixieDust open source library and more at IBM Insight at World of Watson 2016.
IBM Insight at World of Watson 2016, 24–27 October 2016, at Mandalay Bay in Las Vegas, Nevada, is the only place to be for people who work with data. Take a look at this list of top-ten reasons you wont’ want to miss out on one of the most intriguing and innovative events of the year.
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.
Despite big data’s hype, a significant number of organizations are still in a holding pattern—either locked in planning, hesitant to get started or wanting to avoid Apache Hadoop and Apache Spark projects. Complexity and a shortage of skills can exacerbate the situation. Increasingly, organizations
The concluding week of September 2016 offered much excitement in New York City, the backdrop for Strata + Hadoop World 2016 and several key IBM announcements, including the launch of a cloud-based, self-service environment for data science teams. Enjoy some key highlights captured from this