Big Data provides a massive opportunity for companies to create new products, services, and ways of working. Do you know how to use it to your advantage?
Right now, hear from other big data experts about using data to drive smarter decisions, customer experience and more. Plus, register now for a February 18 webcast, Big Data In The Enterprise: When Worlds Collide, to hear IDC Vice President Dan Vesset and Oracle Big Data Strategist Paul Sonderegger discuss the latest research on a new approach to big data in the enterprise and how to make it work for you.
“Data usage and analysis can greatly impact IT costs for an organization. The wrong data management strategy can increase costs exponentially during infrastructure and software integration projects. When executives explore strategies for data management, it is critical to review the key trends that will impact data strategies.” —Subramanian Iyer, senior director of Oracle Insight for Data Center Technologies
“Cloud computing provides enterprises cost-effective, flexible access to big data's enormous magnitudes of information. Big data on the cloud generates vast amounts of on-demand computing resources that comprehend best practice analytics. Both technologies will continue to evolve and congregate in the future” —Satyendra Kumar Pasalapudi, a practice manager in the Infrastructure Managed Services Team at Apps Associates and an Oracle ACE
“A successful, data-driven customer strategy includes three critical elements: a modern data platform, customer information discovery, and rapid operational integration.”—Mark A. Stevens, vice president, Oracle Insight and Customer Strategy
“What this means for companies with big data dreams is that they must embrace this idea and the increased experimentation it entails. They should invest not just in new technology, but also in new skills in experiment design, data analysis and interpretation, as well as management tactics in handling conflicting, data-driven perspectives on the same topic” —Oracle Big Data Strategist Paul Sonderegger
“The first step of the data value chain must happen before there is data: the business unit has to decide on objectives for the data science teams. These objectives usually require significant data collection and analysis. Since we are looking at data to drive decision-making, we need a measurable way to know if the business is advancing toward its goals. Key metrics or performance indicators must be identified early in the process.” —Gwen Shapira, solutions architect at Cloudera and Oracle ACE Director