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Textual data becomes new frontier for BI applications
This article is part of the BI Trends + Strategies issue of Issue 10, October 2012
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 ...
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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.