It’s that magical time of year again, when the nation’s analysts begin to make their 2014 predictions. Mobile will be big (again)! Company X or Y will go down in flames! Apple’s iPhone will lose market share because [insert reason here]!
The future, of course, will prove most of those predictions inaccurate. But everybody seems to uniformly agree that interest and spending on data analytics will only increase over the next twelve months, as more and more companies pursue the dream of greater insight into their voluminous datasets. Research firm IDC, for example, believes that spending on “Big Data” technologies and services will increase by 30 percent in 2014, to $14 billion.
“Here the race will be on to develop ‘data-optimized cloud platforms,’ capable of leveraging high volumes of data and/or real-time data streams,” IDC wrote in its 2014 predictions. “Value-added content providers and data brokers will proliferate as enterprises (and developers) look for interesting data sources as well as applications that help them to understand their customers, products, and the markets in which they exist.”
Big Data platforms will benefit from fresh infusions of retail and social-networking data, as well as increasingly sophisticated algorithms for making sense of structured and unstructured datasets. Simplified dashboards and user-friendly tools could even make data easier to wrangle for employees without formal training in analytics. In many ways, the future (as the cliché goes) looks bright.
But for all the attention paid to tools and infrastructure, there’s precious little discussion about how to use those assets in the most effective way. For any business considering the addition of an analytics platform to core operations in 2014, it’s worth asking the following questions before the commitment of significant money and time:
1. What problems are you trying to solve? There’s a lot of hype in the Big Data market at the moment, with people getting excited over terms like “Hadoop” without really knowing what they mean; before signing onto a very expensive analytics campaign, make sure your little coffee shop actually has a need for mining customer data for granular insight.
2. Do you require a data scientist? If a company plans on plunging into the data-analytics space, having someone onboard with the technical chops to analyze data could prove useful. Bringing in someone with the right credentials could require less time and effort than training staff in analytics, depending on the analytics under consideration.
3. Tools and Tricks. Not all data is created equal; not all tools will get you to insight in the most efficient manner possible. Before engaging in an analytics campaign, it’s worth asking what data your company has available; which datasets can be merged or correlated to produce good insight; and what analytics tools would best suit the issues at hand.
4. Be Skeptical. As with many hyped industries, there’s a lot of confusing chatter right now about Big Data and its capabilities. Approach everything with a healthy dose of skepticism.
However 2014 turns out, analytics could prove a boon for many companies—provided they use the right tools effectively.