big data analytics2014 was the year that talk of Big Data seemed to be everywhere.  From office water coolers to dinner parties, conversation included talk of data, predictive analytics, and the cloud.

2015 looks to have a focus on more actionable results from Big Data. Analytics isn't just about data. It won’t be about tracking and storing every possible metric, but rather about gathering and gaining insights that align with desired business outcomes.

A good example comes from lingerie company, Victoria’s Secret. The company used mobile phone numbers and advanced context-aware technology to alert people when their significant others were searching for or showing interest in a particular product.

In the Victoria’s Secret example, there isn’t that much data being mined, but the relationship between types of data (mobile phone numbers and actions of significant others) contributes to the desired outcome – a sale. With wearable tech and the Internet of Things becoming more prevalent, look for data and actions of consumers both online and in retail stores to become more connected and more tied to desired outcomes.

Some analysts also see 2015 as a year of continued privacy concerns around data. With more devices gathering data, more opportunities will be present for this data to be stolen and used fraudulently.

Other analysts see 2015 as a year that Big Data falls completely short of expectations, and organizations that have collected all sorts of data over the past few years see little to no return on investment from these activities.

It’s only when the Big Data hype subsides that businesses will hunker down and extract true value from data. Much like a physician who can access troves of data on each patient but is most interested in readings of heart rate and blood pressure. Businesses must be aware of the data available and tie that data to desired outcomes – the true lifeblood of any business.

Where do you think the concepts of data and analytics are headed in 2015? Will the hype turn into actionable results? Do you have examples of tying data directly to outcomes in your organization? 

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