EGUIDE:
In this e-guide, read more about the trends that are shaping the demand for AI and how organizations including healthcare service providers and F1 racing teams are leveraging technology on their own terms.
EGUIDE:
In this e-guide, learn about the state of adoption of data analytics in Australia, how Commonwealth Bank is making analytics tools more accessible to small companies and how SAS is prepping its marketers for the data flood.
WHITE PAPER:
Read this paper to learn all the factors you need to consider when choosing a data modeling tool. You will learn about the different model types and how each tool measures up to the demanding needs of your company today and in the future. This paper will lay out all the information you need to make a clear decision on data modeling today.
PRESENTATION TRANSCRIPT:
In today's economic environment, it is imperative that companies begin addressing ways to manage all information assets in an integrated, holistic way. Philip Howard, Research Director for Bloor Research, and Chris Baker, Senior Vice President at Oracle, discuss best practices for obtaining a fully integrated Enterprise Data Management platform.
WHITE PAPER:
The key enterprise risk management (ERM) issue for many financial institutions is to get enriched data in a single place in order to report on it. Learn best practices for data management that are critical for ERM.
WHITE PAPER:
This white paper describes how IBM's Information Server FastTrack accelerates the translation of business requirements into data integration projects. Data integration projects require collaboration across analysts, data modelers and developers.
WHITE PAPER:
This paper analyzes the issues of conventional data warehouse design process and explains how this practice can be improved using a business-model-driven process in support of effective Business Intelligence.
PRESENTATION TRANSCRIPT:
This presentation transcript features speaker Evan Levy, partner and co-founder of Baseline Consulting, a professional services firm concentrating on enterprise data issues. This discussion is about data quality and some of the challenges and pitfalls that are seen during data quality implementation.