Data socialization is a term that’s being heard more frequently, and it’s an attempt to tackle the ongoing (and often mission-critical) process of making sure the right data is in front of the right person. Get this wrong, and despite all of your good intentions it is likely that your strategy for data-driven transformation will become one of the many Big Data projects that fail. It makes perfect sense, really. Facebook, Twitter and LinkedIn have spent billions refining systems for individuals to share data with each other.
But increasingly, businesses are looking to “democratize” this access to data. It has become apparent that embedding data and analytics and ensuring its effects can be measured on every process, is often a more productive approach than attempting to impose data-directives in a top-down, centralized manner.
Adding social functionality to a data strategy means that updates can be shared instantly, edits can be brought to the attention of the right people, and reach, interaction and other social metrics can give an accurate picture of the value being gained from any data resource or initiative.
If BI and analytics-enabling platforms are able to successfully roll out a culture of data-driven experimentation and innovation within modern enterprises, it is likely that they will do it by paying serious attention to the way social media has become enmeshed into everyday lives.
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