The concept of big data fabric represents a fundamental change in how businesses approach data storage, fast data analytics, and streaming data to make it much easier, faster, and simpler to retrieve actionable information and increase the value that you can get from customer data.
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
Cognitive technologies such as advanced analytics and artificial intelligence are emerging as vital tools for achieving digital transformation outcomes. Learn more about the role of cognitive technologies from early adopters in the recent IBM Cognitive Advantage report and how they can be used to
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
Organizations looking to transform their operations can turn to data science for an approach that offers the ability to predict events and behavior, prescribe actions, derive insights and make informed decisions. Learn more about how you can tap into the power of data science through predictive
One of the chief data officer’s primary responsibilities is to support the company’s strategy for monetization. Learn how investing in essential technologies can help your team create a data strategy that aligns with your organization’s monetization strategy to empower the business as a whole.
We’re all aware of how data streams at us from anywhere and everywhere, and all the implications that continuum entails. But when attempting to derive value from all that data—the data we can access as well as the data we don’t have access to—CIOs need an innovative advantage to help their
Take a peek at the future of data science in this discussion with five thought leaders in the data analytics industry, the second installment of a two-part interview recorded at the IBM Insight at World of Watson 2016 conference.
Take a peek at the future of data science in this discussion with five thought leaders in the data analytics industry, the first installment of a two-part interview recorded at the IBM Insight at World of Watson 2016 conference.
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."