Information Management and Analytics
Documents
A Guide to Building a Metrics Driven Organization
| Date added: | 12/13/2010 |
Author: Dr. Fern Halper, Partner
Sponsored by PivotLink
A guide describing what to consider when developing metrics. The importance of metrics, how to think about metrics and KPIs, how to develop metrics, case studies of companies that were successful building out metrics strategies. Metrics, BI, dashboards.
Content Management Meets Text Analytics
| Date added: | 05/01/2009 |
Author
Dr. Fern Halper, Partner
Sponsored by EMC
Information is the lifeblood of any company. While organizations have made significant progress in analyzing their structured data (such as sales figures and number of complaints), the reality is that most company information is unstructured. This unstructured information includes claims, contracts, patents, call center notes, clinical trial records, and survey responses, which are often stored in enterprise content management systems. Content management systems are a treasure trove of information since there is a significant amount of insight that can be derived from this unstructured data. The flip side of this is that there is so much enterprise information that a knowledge worker (e.g. a product manager, marketing manager) can quickly become overwhelmed and not make the best use of it.
From Business Intelligence to Business Optimization
| Date added: | 04/01/2009 |
Authors
Dr. Fern Halper, Partner
Robin Bloor, Partner
Sponsored by IBM
Companies run on information. And in today’s dynamic and changing market, businesses
need trusted and actionable information more than ever. In order to be successful,
businesses must maximize their information assets to capture new opportunities and
remain competitive. What does a company need in order to do this?
Expanding the Boundaries of Enterprise Content Management Systems
| Date added: | 10/01/2008 |
By Dr. Fern Halper, Partner
Sponsored by IBM
The technology needed to implement an information management strategy will provide access to and analysis of systems data and the vast amount of unstructured data or “content” sitting in content repositories.
Using Data Models to Maximize the Value of Your Data Warehouse
| Date added: | 06/01/2007 |
Authors
Dr. Fern Halper, Partner
Marcia Kaufman, COO and Principal Analyst
Judith Hurwitz President & CEO
Sponsored by IBM
The typical IT organization often has trouble understanding the data requirements from a business unit as well as the ovall corporate context.
Because of the dramatic changes in the financial services industry, companies are looking for technologies that help them streamline their business processes and systems, and leverage their business information across the organization. Hurwitz & Associates reviewed IBM’s approach to leveraging data models to accelerate successful data warehouse deployments. In-depth interviews with customers of IBM’s Insurance and Banking Data Models provided the basis for this research. The companies interviewed found tangible and business benefits using the IBM technology. Key findings included:
