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Talking SMAC: Revisiting social, mobile, analytics and cloud

Jonathan Hassell | May 5, 2015
If your IT team doesn’t have a SMAC roadmap, you may find your company drifting off-course in 2015 and 2016. Here’s brief refresher course on SMAC.

In the beginning of SMAC, social networks were still figuring out just what assets they actually had. But in 2015, there are now companies whose sole job is to sift through social data and find emerging clues and patterns. Facebook has a billion users, Twitter has hundreds of millions and LinkedIn is the de facto professional networking site. We will continue to see these social networks monetizing content -- whether directly (through ads) or indirectly (to convince people to use their APIs) -- into the latter half of 2016 and beyond.

Thanks to smartphones, hundreds of millions of people have the equivalent of a late-1990s supercomputer in their pocket. The power that is inherent in such technology is both obvious and striking. Witness the data Apple Pay allows Apple, credit card companies and merchants to gather: location, time and date, identity, available cards, available balance, type of phone, sequence of purchases, ratio of Apple Pay purchases to regular card-style transactions, wireless carrier of choice, average battery charge (great for considering what impulse buys happen after a long day out) and even more. So many data points, and they are only increasing.

With all of these increasing data points, analytics solutions are scaling to match. Between machine-learning services, which let computers march through data to learn patterns and insights, and the advent of new types of databases, analytics grows more powerful by the day. In particular, there are now graph databases -- databases that are built, not to relate rows and tables, but to relate entities with one another, such as a customer to a specific book or a movie to a specific subscriber (in the case of Netflix). These graph databases have changed the big data/social data game. Databases themselves are now smarter and lending themselves more to analytics applications.

The cloud grows ever stronger. Microsoft has put Hadoop up in the cloud and has made Azure Machine Learning available for data scientists to plow through data and have the service itself suggest comparisons, predictions and key points. Amazon and Google are playing catch-up here in the specialized data services department, but from a raw compute capacity (see "What's New in the Public Cloud), there has never before been a time when you could acquire fast computing at mere pennies per hour. Any of these services will let you scale up and down your capacity and compute power as necessary, and even the heaviest workloads can benefit from running on someone else's millions of servers.

The Last Word on SMAC
SMAC is growing stronger and smarter every day. Do you have a SMAC strategy? How will you grow yours to deliver real, positive benefits to your business? What is your road map? How will you monitor this trend going forward?

If you can't answer these questions, it's time to make sure everyone on your IT team is fluent in talking SMAC.


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