New IBM Watson Data Platform and Data Science Experience
Yesterday IBM announced a new IBM Watson Data Platform that combines the world’s fastest data ingestion engine touting speeds up to 100+GB/second with cloud data source, data science, and cognitive API services. IBM is also making IBM Watson Machine Learning Service more intuitive with a self-service interface.
According to Bob Picciano, Senior Vice President of IBM Analytics “Watson Data Platform applies cognitive assistance for creating machine learning models, making it far faster to get from data to insight. It also, provides one place to access machine learning services and languages, so that anyone, from an app developer to the Chief Data Officer, can collaborate seamlessly to make sense of data, ask better questions, and more effectively operationalize insight.”
Back when IBM Watson beat Ken Jennings at Jeopardy, the power processor ran on 100 calculations, a million times per second. Now, Picciano said, it does 1 million calculations, a million times per second.
IBM Watson Data Platform nicely integrates IBM Cloud Data Sources, Data Science Experience, Watson APIs, and much more on the IBM cloud, Bluemix.
Persona-based capabilities within IBM Watson Data Platform enable a high level of collaboration across data scientists, data engineers, business analysts, and developers. The platform provides one collaborative environment for multiple roles. Within that environment, experiences designed for task-specific elements to further streamline connections and data discovery.
Another differentiating factor for IBM’s offerings is advancement of intelligent Industry Models. When this all gels together…it will be even more amazing.
IBM’s Data Science Experience is a cloud, browser-based environment for creating and deploying machine learning models in a guided experience. Machine learning models authored in Jupyter notebooks can be imported from a growing community library, pre-built industry solutions, or created from scratch.
IBM’s investments in Apache Spark, Bluemix cloud, cognitive computing, and several innovations developed by IBM Research were evident while reviewing these solutions. Like other massive technology vendors embracing open source, IBM is leveraging an expanding, familiar analytics ecosystem of Spark SQL, Python, R, Java, and Scala.
In the broader IBM cloud data platform architecture, I noted a fabulous project for global metadata management and collaboration using Apache Atlas that is worthy of a dedicated future article.
