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Data science holds tremendous potential for organizations to uncover new insights & drivers of revenue & profitability. Big Data has brought the promise of doing data science at scale to enterprises, however this promise also comes with challenges for data scientists to continuously learn & collaborate. Data Scientists have many tools at their disposal such as notebooks like Jupyter & Apache Zeppelin & IDEs such as RStudio with languages like R, Python, Scala & frameworks like Apache Spark. Given all the choices how do you best collaborate to build your model & then work through the development lifecycle to deploy it from test into production?

IBM Data Science Experience (DSX) provides you with the environment & tools to solve your business problems by collaboratively analyzing data. DSX is now part of the IBM Watson Data Platform which is an integrated platform of tools, services, & data that helps companies accelerate their shift to become data driven organizations. The platform can consume & work on any data source: on-premises or cloud, structured or unstructured, in-motion or at rest, internal or external to an organization. It has five main data & analytics functions (ingest, persist, analyze, deploy, & govern) that can be exercised in any order & any combination. The compose-able services provide APIs that enable customers, business partners, & system integrators to build on & extend these capabilities.With IBM Data Science Experience, you can create Python, Scala, & R notebooks to analyze your data, collaborate with others on your notebooks, add comments, & view a history of your notebooks. You can create a machine learning flow, which is a graphical representation of data, by using the Flow Editor to prepare or shape data, train or deploy a model, or transform data & export it back to a database table or file in object storage & Use visualization's in your notebooks to present data visually to help identify patterns, gain insights, & make decisions. Many of your favorite open source visualization libraries, such as matplotlib, are pre-installed & available on DSX. Data Science Experience machine learning flows use Apache Spark machine learning (SparkML) algorithms to build models. RStudio, included in IBM Data Science Experience, provides an IDE for working with R. DSX has a thriving community which contains resources to help you learn more about data science. Join us on to see an use case driven demo of DSX & how it can help you get started on and/or accelerate your data science journey.

Agenda:

- 6:00 pm: Pizza & networking
- 6:30pm: Why Data Science on Big Data? Data Science at Scale Demo

Q&A

Speakers:

Artem Ervits, Sr., Solutions Engineer, Hortonworks

Rahul Daterao, Enterprise Cloud Architect, IBM
Rahu is an Enterprise Cloud Architect at IBM & a Watson Data Platform Cloud Specialist with expertise in Big Data, Elastic Search & other NoSQL technologies. His 20+ years experience includes being hands-on CTO for two NYC based startups (Appssavvy & KickApps). He is an open source technology evangelist, engineer, developer & enjoys to collaborate with all those passionate & interested in driving innovation.(https://www.linkedin.com/in/rahul-daterao-baa9ab1/)