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Description:

You've identified a real business need for a big data project — now what? How do you articulate and justify this need, in order to fund the initiative?

When pitching a big data strategy to company stakeholders, you need to know your audience — understanding each role, and its accompanying needs and concerns, is critical. For instance, business analysts might want a SQL-based solution that integrates with current BI and reporting tools; business owners may want to uncover new revenue streams or increased operational efficiency; and data scientists may look for tools to creatively explore large volumes of data, quickly.

Having a successful big data strategy can deliver massive benefits to the business — new products and services, reduced customer churn, and cost reductions, to name a few — but first you must know your audience's interests, and connect those interests to business imperatives. Thinking in terms of revenues, costs, and competitiveness can help you communicate your vision to technologists and business stakeholders alike, and explain what’s required to make the project succeed.

Join Larry Lancaster, Founder of Zebrium, for a blueprint on how to get buy-in for your big data project. In this webcast, you'll learn how to successfully:

• Envision the business value of your big data project
• Select the right use-case to relay your message
• Identify how the business can monetize new analytics capabilities
• Communicate the benefits of your data strategy, to different audiences

About Larry Lancaster, Founder of Zebrium

Larry is well-known in the storage array industry as a visionary of the IoT approach to enterprise storage. Before founding Zebrium, he was the Chief Data Scientist at Nimble Storage, founding the company's data science team and architecting/implementing their peta-scale platform for automation and analytics. The InfoSight suite of automated services are widely regarded as the industry's gold standard for PLM, support, and service delivery; the team and Larry painted the originals using a broad palette of big data, analytical modeling, simulation, forecasting, visualization, and relational tools.

Larry has been blessed to be surrounded by smarter people. They've inspired him to receive a number of patents and publish a number of peer-reviewed and trade-secret articles in neuroscience, reliability analysis, and industrial applications of queueing theory. He's also been fortunate enough to found NetApp's Engineering Informatics and Support Automation group as Senior Engineer, invent Glassbeam's ETL-focused SPL technology as CTO/co-founder, and receive a leadership award from the International Congress on Neural Networks as graduate student.