This is a white paper on the business applications of BigInsights.
For your convenience, here is the executive summary:
Companies are hyper-connected to their customers and partners every minute of every day. With that connectedness comes exploding volumes of data, of greater variety and at a greater velocity. These flows are so large that they define a new category: big data. They offer tremendous potential for deep insights that support smarter decisions and increased revenue. How can businesses benefit from these information flows? How can they harness big data to generate new insights quickly and cost-effectively, while building off their existing information management approaches and strategies?
Imagine if you were able to:
- Build sophisticated predictive models from the combination of existing information and big data information flows, providing a level of depth that only analytics applied at a large scale can offer
- Broadly and automatically perform consumer sentiment and brand perception analysis on data gathered from across the Internet, at a scale previously impossible using partially or fully manual method
- Analyze system logs from a variety of disparate systems to lower operational risk and optimize advertising content targeting
- Leverage existing systems and customer knowledge in new ways that were previously ruled out as infeasible due to cost or scale
To be innovative, companies are looking for new ways to grow by finding value in this data and challenging traditional business models to provide greater efficiencies, increase revenue, create new value-add services, and in some cases transform how they do business. IBMÂ® InfoSphereâ„˘ BigInsights enables a new class of solutions associated with big data challenges to help organizations optimize their business. InfoSphere BigInsights is an analytics platform that delivers unique IBM Research, emerging technologies and capabilities on top of Apache Hadoop open-source framework, enabling new solutions on a business-ready platform fully supported by IBM.