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
Many of us might be surprised to learn that some of the most familiar brand names around started off with other names. IBM recently renamed IBM DataWorks—its flagship, self-service data preparation offering—to IBM Bluemix Data Connect. Get a glimpse of it in this brief overview, and discover how
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?
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
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.
The movie Deepwater Horizon that depicts the oil spill disaster of the same name serves as an example of how government agencies and corporations need to collect a lot of data and disseminate information immediately as events quickly unfold. Not only are all parties involved asked for a tremendous
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.
The Internet of Things (IoT) is making inroads in all areas of life, expanding the opportunities for each new generation of global citizens. What’s more, cloud technology is bringing IoT capabilities to people around the world, bringing them together in a new world of data.
The benefits and pitfalls of different cloud deployment architectures can be intense topics of conversations spanning a wide range of industries. Some discussions foster new approaches to consider, and others make strong arguments as to which approach is well suited for different, industry-specific
Although formerly exclusive to the IBM Hadoop Platform, the extension of Big SQL to the Hortonworks Data Platform (HDP) meets the challenge of complex data warehousing queries on Hadoop. See what Paul Yip, worldwide product strategy for Hadoop and Spark at IBM, has to say about what this transition
Database migration is not any database administrator’s idea of fun—not even close. By far, the database migration status quo can be the least interesting and most dreaded part of the job. Check out an advanced self-service, ground-to-cloud database migration offering for handling database migration
Many marketing concerns have seen the light when it comes to the application of big data analysis as a means of outthinking the competition. Discover three best practices for implementing big data analytics for good data science in marketing initiatives.
Chris Snow, a data and application architect, enjoys helping customers with their data architectures and is working extensively on an open source app project in his spare time. Hear what Snow has to say about his IT experience spanning several industries, his current efforts with customers and his