Access "Textual data becomes new frontier for BI applications"
This article is part of the Issue 10, October 2012 issue of How a powerful business analytics strategy can raise ethical issues
For years IT and business intelligence (BI) teams have focused on repetitive structured transaction data. But structured data represents only about 20% of the overall data in most companies. That means they’re missing out on the business insights that can be found in the other 80%—the unstructured data. It’s time for a change. New technology allows unstructured data to be included in the decision- making process. For example, standalone text analytics tools can be used to look for patterns in text data and assess its meaning and sentiment. Organizations can also now place text in standard relational databases, so it can be stored in data warehouses for mainstream BI tools to analyze. Having this previously unstructured data available for analysis presents valuable information that can be used to make better decisions. In addition, new business opportunities can be uncovered that would never see the light of day by analyzing conventional record-based data only. Here are a few examples of the kinds of text data that companies can now use more effectively: ... Access >>>
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Power, reach of analytics pose new ethical dilemmas
by Frank Buytendijk
Analyze, analyze, analyze. That’s the mandate in many companies. But to avoid negative repercussions, it’s wise to proceed with caution and consider the moral issues created by powerful analytics tools.
Textual data becomes new frontier for BI applications
by W. H. Inmon
Unstructured text data can hold valuable insights, but analyzing it has been a challenge. New tools are changing that, opening up additional data-analysis opportunities and enabling better decision making.
- Power, reach of analytics pose new ethical dilemmas by Frank Buytendijk
BI competency center brings coordination -- but with complications
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- BI competency center brings coordination -- but with complications by Alan R. Earls
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