There is so much talk about data as a new natural resource. The amount of data organizations and citizens across the globe produce, is authored in many systems and consumed by various organizations and users in different formats. This begs the following questions: Who owns this data? And why it is
Today’s businesses need a culture of collaboration that empowers knowledge workers to glean cognitive insights from data that help transform and modernize operations. See how cloud-based platforms and solutions enable data scientists and other experts to exploit artificial intelligence, machine
Elderly care is on tap to be a critical need in the coming decades. See how Caregivers.com is using cloud computing and mobile technologies to provide greater choice for families and higher wages for in-home caregivers.
The unprecedented evolution of social media data’s influence on business can have tremendous impact on how customers are integrated into organizational goals and practices. See why more organizations than ever are using social media data to take a customer-centric approach to evolving their
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
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
Historically, Master Data Management (MDM) projects have focused on creating a single view of the truth that can be consumed by business processes. Learn more about how the evolving need to utilize MDM serves as catalyst for a new solution extension offering a managed data preparation and data
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
Women might make up 30 percent of the workforce at technology companies—for now—but they’re a force to be reckoned with no matter their numbers. Are you trying to balance work and life while advancing in your career? Or are you considering pursuing a career in tech? Find how IBM is embracing the
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.
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
Automation can be a great solution for highly manual processes, but its implementation has its detractors. Can robotic process automation be successful in providing an artificial intelligence solution that includes machine learning for further streamlining typically manually intensive processes?