There is a widespread and accepted concept that the relatively low uptake of enterprise Business Intelligence (BI) software (<20% within enterprise-licensed organizations) is a result of problems with data quality, ease of use issues, and a more or less general resistance to it in favor of Excel and/or massive fixed reporting. While there is an element of truth in this, it obscures a more insidious problem that Hired Brains has uncovered in continuous research over the past 10 years.

People don’t understand the data, they don’t know how to integrate it into the work they do and, thus, they perceive it to be irrelevant.

BI is getting a big boost, especially in the areas that bypass knowledge workers, such as embedded analytics in operational systems, event processing, etc. But the core BI industry is still a $20 billion industry, largely concentrated on large organizations, and it needs a new approach.

Recognizing the problem, somewhat, of lack of understanding of the data, the industry has responded with Master Data Management (MDM) and Data Governance, but both approaches are insufficient because they lack the representational framework to actually be a runtime MODEL of the data, not just a picture of it (as it is in most forms for metadata and MDM).

The solution is to implement semantic technology as the underlying representation of data and relationships in BI and associated tools.

This session will:

• Explore the specific problems caused by a BI environment lacking a semantic framework
• Describe how semantic technology will encourage wider and more predictive use of BI
• Review how some vendors are already moving in this direction, why some never will, and look at some small start-ups and what they’re up to