Social Media and Corporate Data Warehouse Environments: New Approaches to Understanding Data

Social Media and Corporate Data Warehouse Environments: New Approaches to Understanding Data

Debora S. Bartoo (Saint Joseph’s University, USA)
Copyright: © 2012 |Pages: 12
DOI: 10.4018/jbir.2012040101
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This paper argues that organizations need to prepare for the integration of social media data into their data warehouses in order to fully understand their customers. Social media has quickly gained acceptance in its adoption and use and firms are eager to get their hands on it to better understand customer sentiment. However, social media data is different and more complex than traditional data and most data warehouses are not structured in a way for BI applications to easily make sense it. As a result, it is becoming critical for business intelligence teams to begin to understand the challenges this data presents and to better plan for the integration of this information into corporate data warehouses.
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“Social media is that which allows anybody to communicate with everybody.” In other words, it is consumer-generated content distributed through easy-to-access online tools (Sterne, 2010). Examples include You Tube, Facebook, LinkedIn, blogs, Twitter and many more. The web has become a focus group of experts who believe their views are important and want to be heard. Gaining insights into this data isn’t like methods used for traditional structured data. Social media data mining is more complex because it is about interactions. It is about conversations. It can happen with anyone anywhere across the world and, it happens instantly. It is unstructured. It doesn’t fit neatly into a data field. It doesn’t have pre-defined answers.

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