Just as data analysis strategies must be highly adaptable

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So must development strategies. Given the high dynamic nature of data, traditional data warehousing techniques cannot be used for data integration. Here, data speed and volume are more important than accuracy.

Integration between social data and enterprise data presents an interesting challenge. Most mature organizations have data quality policies for their enterprise data, while social data is typically very raw and can have duplications Armenia Mobile Database and contradictions. A good social analytics strategy should consider appropriate integration points and mechanisms between enterprise data and public social data, organizing them in a way that is most useful to the business.



Technologies
A social analytics environment requires a different set of technologies than what is typically found in a data warehousing and BI infrastructure. Candidate technologies should include tools for: data discovery and harvesting; filtering and retention; analysis and visualization. Depending on strategic goals, some technology for metadata management may also be needed.

Discovery and harvest.