Informatica 9.5 for Big Data Challenge #2: Social

Social networking is becoming inescapable. It has become mainstream faster than almost anyone could have predicted (other than perhaps Mark Zuckerberg.)

Full disclosure:  I hardly ever use Facebook. Perhaps as a working mom with two young children, keeping up with former high school classmates is a luxury I can’t afford (or don’t want). But I use other types of social media extensively. I use LinkedIn for professional networking, recruiting, knowledge sharing and development. I use Twitter to communicate with customers, analysts and industry peers. I use several local online moms’ communities for advice on toddler tantrums, teething and preschools.

With more and more people interacting via social networks online, more and more social data becomes available to better understand behavior, sentiment and relationships. The data privacy issues are significant, but as they get sorted out over time, many businesses will have the opportunity to mine this data to improve their customer and market knowledge. The applicability is most obvious for consumer-oriented companies such as retail, entertainment, travel, hospitality and consumer packaged goods.  But B2B buyers are also moving their professional activities, including vendor evaluations, into the social media realm, so it won’t be long before B2B companies also ramp up their social media efforts.

Of course, with the volume of social media activity that is generated on an hourly basis, the volumes can be overwhelming. And the data is almost entirely unstructured, making it very hard for traditional systems to process. Social data is one of the key elements driving the overall big data phenomenon, as new data processing platforms and paradigms are required to find the needle in the massive haystack of social network interactions.

That’s where Informatica 9.5 comes in.  In addition to expanding pre-built connectivity to social data sources, Informatica 9.5 introduces a few critical pieces of functionality. First, natural language processing capabilities allow you to extract entities and meaning out of unstructured text that may be in a LinkedIn profile, or in a web posting. Second, social MDM enables you to extract information on customer preferences, profiles and relationships out of social networks such as Facebook (on an opt-in basis), and integrate it with existing customer master data to create a truly comprehensive customer profile. Third, in many cases IT groups are turning to the Hadoop stack to process social data, given its large volumes and highly unstructured nature. Informatica 9.5’s support for Hadoop, enabling both increased interoperability with traditional applications and a leap in development productivity for Hadoop, will be a big boost to social data processing.

There’s still a long way to go to bring social data into the mainstream enterprise, in part due to concerns over privacy and the potential “creepiness” factor of mining social data. But as those concerns are worked through, Informatica technology can ensure you can separate what data is useful from what is worthless, and fully utilize the relevant data to deliver new insight and value to the business.

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