Data Quality Management: The Key to Successful Predictive Analytics

Data Quality Management: The Key to Successful Predictive Analytics


Organizations of all types and sizes are enhancing their business intelligence (BI) strategies with predictive analytics. Forrester Research Inc. found that business analytics is the fastest-growing segment of global IT software, with close to 70% of companies polled expressing a strong interest.

Traditional reporting and analysis provide you with a rear-view perspective of events that have already occurred. With new technologies you can foster a more proactive approach to decision-making. These techniques apply to data mining and statistical analysis of large volumes of both current and historical data.

Read this white paper to uncover the importance of data quality management as it relates to predictive analytics. Also, explore various methodologies for assessing and improving data quality, and learn best practices in preparing data for predictive analysis. This paper also presents a real-world scenario of how poor data quality would negatively impact predictive modeling efforts.

Information Builders
05 Dec 2011
05 Dec 2011
14 Page(s)
White Paper
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