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.
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.
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
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
The evolving Internet of Things is fueling a rise in the adoption of streaming analytics across a growing number of industries. Learn more about the rising adoption of real-time streaming analytics in industries and top use cases cited in the recent “Bloor Market Report on Streaming Analytics 2016.”
The transformation of the streaming analytics market demonstrates how business process automation is being driven by innovative open source projects and an ever-increasing world of sensor-derived data. See how IBM fared among 14 commercial providers of streaming analytics in a recent Bloor Market
Maybe classifying data as structured or unstructured isn’t so simple. What is structured to some may not be structured to others and vice versa. When it comes to the business value of data, consider another way to look at data—whether it is repetitive data or non-repetitive data.
When I spoke with Derek Schoettle, General Manager, Analytics Platform Services, the subject of open source capabilities came up a few times. Data is going to change the culture of business, and in fact it becomes the culture when you truly embrace it.
Insights from CIOs can reveal a lot about the industries in which they operate, and hearing from IBM’s CIO is no exception. Check out these highlights from a recent podcast featuring Jeff Smith, CIO at IBM, who offers a glimpse at his idea of focusing on culture, a story of transformation, the CIO’
Data analytics is fueling new strategies in law enforcement from the federal level down to local departments. Whether it's finding patterns across time and location, predicting new threats or linking resources to responders during major events, data is the future of proactive emergency plans.