“Data Science for All webcast”- An IBM Creation

Undergoing data science journey for experiencing best possible data expertise and exploring the tools optimally, IBM created the ‘Data Science for All webcast’. Rob Thomas, IBM VP of Analytics, and Katie Linendoll recently hosted the live broadcast to spread awareness among targeted masses regarding the IBM approach to enterprise data science. The panel within the broadcast was seen discussing the issues confronted by businesses trying to look for appropriate solutions around consuming data, and practicing data science with that data.

It could be drawn from the discussion that enabling data science is becoming increasingly important as an essential asset to every company, and in every industrial sphere. FiveThirtyEight’s Nate Silver shed light about that importance, the value that data science is capable to provide in informing his own writing. In this writing he covered topics across sports and politics.

In the context of the need for data science, Rob and Katie held long discussion about the fact that data literacy for everyone to acquire is the need of the hour. The leaders of what Galvanize Director of Data Science Nir Kaldero dubs the "Fourth Industrial Revolution" will be those who have acknowledged the importance of data literacy and embraced data as an asset. With more than 80% of consumable data stuck behind the firewall, however, the enterprise machine learning space requires appropriate assistance.

Data analysts, machine learning engineers and data scientists require a multi-cloud workbench solution. These separate functions need to work in close collaboration and data science does require becoming a team sport. IBM Data Science Experience happens to be the workbench that facilitates that collaboration all through every possible team, data, tools and deployments.

The IBM Data Science Experience release is the team-wide solution to collaborative machine learning. It can be described as a tool set formulated to target data scientists, with its open-source project compatibility and hassle-free deployment. It is further found to be designed to enable the non-coder; who doesn’t know languages like Python, Scala, or R. Integrating data science practices definitely can become easy with IBM Data Science Experience.

IBM has tried going beyond tight integration, featured within the release announcement, with the leader in the big data and enterprise Hadoop — Hortonworks. Now one can find an enterprise solution for making quality use of those vast lakes or dark data. Not just companies now can explore their on-premises data and design their machine learning models behind their firewall, with the help of IBM Data Science Experience, but they also can publish those models for consumption purposes on a public cloud.

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