While SMAC (social, mobile, analytics and cloud ) concept crystalized only in the past couple of years, buy this new area in data warehousing and data analytics has been growing -- and improving -- every day.
Revisiting SMAC will be useful for many CIOs as they look into the second quarter of 2015 through 2016 and beyond. What has changed? What has improved?
What makes up SMAC?
A quick review: SMAC is a concept where four ingredients come together to allow businesses to derive new insights about their customers' preferences and behavior. Those ingredients include the following:
- Social networking. Social data includes information harnessed from the likes of Twitter, Facebook, LinkedIn and Yammer to uncover the "timelines" of a customer base: What they talk about, what they are interested in, what they are looking forward to and what are their basic family demographics, all of which can especially be gleaned with the help of a vendor like DataSift.
- Mobile devices. Mobile devices are the cornerstone of how new business is being built. Mobile devices allow users to constantly update their profile, stay aware of deals and promotions, and track locations and buying habits by virtue of connecting to various wireless signals and near-field communication (NFC) devices.
- Analytics programs. As databases have grown larger and processors and memory have become capable of chewing through hundreds of millions of records in a short time, we have begun to see how analytics can do more than just track clicks. Analytics can establish links between entities and make intelligent predictions about customer behavior based on knowledge a system has about a customer -- knowledge that has been informed by social networking.
- Cloud computing. The cloud element of SMAC refers to the capability a business has to spin up vast amounts of capacity that are paid for by the minute or hour. Businesses do not need to spend millions of dollars building another data warehouse -- they simply rent it from a cloud provider, do their work and turn it off. When the business environment changes, they simply spin up another cluster in the cloud, pay another few hundred dollars and continue building insights.
The convergence of these technologies means there has not been a better time in history to get deep insights and predictive capabilities into your customer base. As a CIO, it is your duty to deliver to your organization the best business-enhancing tools you can -- after all, you are more than Patch Tuesday and email backup restorers. SMAC is an area where CIOs can deliver tangible results to a business.
What is new in SMAC in 2015?
How have improvements and enhancements in each of the contributive areas of SMAC really bolstered the end game for organizations harnessing the power of a SMAC strategy?
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.