Hype surrounding Big Data is strong enough that some organizations may feel pressured to pursue investments that canít be clearly justified from an ROI perspective. IT must be wary and avoid the trap of rushing into Big Data, because a poorly conceived strategy can fail to deliver the considerable benefits that Big Data offers.
At this one-hour webcast, youíll learn:
The steps required to build a detailed plan to ensure your Big Data project meets expectations
How to define the correct metrics to accurately and successfully measure your results
Selecting the software platform that can scale to meet current and future Big Data requirements
If youíre in the C-suite, or youíre an IT manager who is delivering Big Data solutions on a hands-on basis, this webcast will give you the latest intelligence and best practices to ensure your success.
Saul Sherry, Editor, Big Data Republic
Saul Sherry is Editor of Big Data Republic. He has a long history of reporting and commenting on design and technology. He focuses on how technological innovation can improve the enterprise, cutting down on waste, inefficiency, and missed opportunities. In the field of big data, his particular interest is in the ways it can reveal to us the intelligence that lurks below the surface of the everyday and how we can use this to improve lives. If you have questions about Big Data Republic, or want to inquire about being a moderator or a blogger, please feel free to email: email@example.com.
Dr. Thomas C. Redman, President, Navesink Consulting Group
Dr. Thomas C. Redman, "The Data Doc," is President of Navesink Consulting Group, based on the Jersey Shore. He has helped hundreds of organizations and thousands of people understand the importance of data, start their data programs, and make order-of-magnitude improvements. In doing so, they lower costs, increase revenues, improve customer satisfaction, and make more confident decisions. His fourth book, Data Driven: Profiting From Your Most Important Business Asset (Harvard Business Press) is a Library Journal Best Business Book of 2008. Prior to forming Navesink in 1996, Tom started and led the Data Quality Lab at Bell Labs. There, he and his team were first to extend quality principles to data and information. He is an internationally known lecturer and the author of dozens of papers. He holds two patents.
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