Introducing Notebooks: A power tool for Data Scientists
Fast, flexible and collaborative data exploration and analysis: Data exploration and analysis is a repetitive, iterative process, but in order to meet business demands, data scientists do not always have the luxury of long development cycles. What if data scientists could answer bigger and tougher questions faster? What if they could more easily and rapidly experiment, test hypotheses and work more collaboratively on interactive analytics.
The pressure to be this responsive gets passed to experts with deep analytical skills, most notably the data scientist. The data scientist must grapple with difficult constraints and revise cumbersome development processes in order to meet the business’s high expectations. For both the data scientist and business stakeholder, wrong turns and dead ends are often the rule, not the exception.
Read this white paper and learn how to quickly spot errors, change course, and find the right path to the conclusions and insights that could be game changers for your business.
Content provided by IBM