Big data and analytics help insurance companies identify the next best action for customers. With the right solutions, companies can extract, integrate and analyze a large volume and variety of data, from call-center notes and voice recordings to web chats, telematics and social media.
Big Data Research
AARP needed to transform its traditional BI infrastructure into a dynamic, blazing-fast environment which could assist with improved member documentation and recognition, accurately match services and product offerings to member needs and deliver value-added packages to targeted customer demographics.
With IBM Big Data & Analytics, AARP modernized its business intelligence infrastructure ultimately achieving a 347% ROI in three years.
This new commissioned study conducted by Forrester Consulting on behalf of IBM dives deeper into the trends surrounding big data and analytics to strategically examine the goals, challenges, and impact associated with customer analytics.
In today's competitive marketplace, executive leaders are racing to convert enterprise insights into meaningful results. Successful leaders are infusing analytics throughout their enterprises to drive smarter decisions, enable faster actions and optimize outcomes. In this exciting new piece of research, the IBM Institute for Business Value surveyed 900 business and IT executives from 70 countries. Through our research, we identified nine levers that together enable organizations to create value from an ever-growing volume of data from a variety of sources – value that results from insights derived and actions taken at every level of the organization.
How data lifecycle management complements a big data strategy
Information integration and governance solutions must become a natural part of big data projects. As the foundation of the IBM big data platform, IBM® InfoSphere® Optim™ provides market-leading functionality across all the capabilities of information integration and governance, including a comprehensive range of capabilities enabling companies to properly manage big data and implement best practices for enterprise-scale data lifecycle management.
While the term “big data” has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades, leading the way with data integration, management, security and analytics solutions known for their reliability, flexibility and scalability.
The end-to-end information integration capabilities of IBM® InfoSphere® Information Server are designed to help organizations understand, cleanse, monitor, transform and deliver data—as well as collaborate to bridge the gap between business and IT.
This research report from Forrester Consulting, commissioned by IBM, examines the growing role of information and integration governance (IIG) to move big data from the realm of possibility to the reality of business outcomes. Forrester Consulting surveyed 512 business sponsors, business intelligence professionals and IT decision makers, finding that organizations are embracing IIG on the path to big data. This report examines successful IIG practices and offers insight for those on a big data journey.
This is a research report by noted industry analysts Claudia Imhoff, Intelligent Solutions, Inc., and Colin White, BI Research. IT leaders need to review and enhance their information architecture to support requirements fueled by big data, advanced BI and other innovations. Examine the What, the Why, and the How behind these innovations to exploit the potential for improved business efficiency with IBM DB2.
Aberdeen has long illustrated the benefits of well-managed, trustworthy data, and the problems associated with poor data quality. As data volumes rapidly expand and data environments become more complex, what were once small nuisances evolve into massive, company-wide problems. In order to avoid these pitfalls and achieve better business efficiency and operational performance, top performing organizations have found it necessary to invest in tools such as data security, master data management, data quality, data lifecycle management and data integration. Using research collected from December 2009 to December 2012, Aberdeen examines the hidden financial penalties for lapsed information governance and untrustworthy data.
Cost/Benefit Case for IBM PureData System for Analytics: Comparing Costs and Time to Value with Teradata Data Warehouse Appliance
Three-year costs of ownership for use of PureData System for Analytics N2001 appliances average 36 percent less than for Teradata equivalents. Comparisons are for comparable applications and workloads. This report applies both sets of metrics to cost comparisons for IBM PureData System for Analytics N2001 and Teradata Data Warehouse Appliance 2700 in four representative installations in digital media, financial services, retail and telecommunications companies. Results are based on input from 17 organizations employing Teradata Data Warehouse Appliances and 21 employing IBM PureData System for Analytics appliances in comparable roles.