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.
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."
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?
IBM extended Big SQL, which was formerly exclusive to the IBM Open Platform (IOP), to the Hortonworks Data Platform (HDP) in September 2016. I recently spoke with Berni Schiefer, an IBM fellow in the IBM Analytics group, to learn more about the offering and the ongoing IBM focus on SQL.
Historical application of vector mathematics and the study of unstructured text data can be an important approach to understanding and actualizing the value of data. See how mathematical exploration of text data can unearth insight that translates into enhanced decision making.
Hear from Nancy Hensley, director of offering management for IBM Analytics who speaks with Rob Thomas, VP of development for analytics on the subject of business transformation and a discussion of the data maturity curve.