Big Data… I’m confused big time!

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Understanding cloud computing and big data

This cloud computing thing is piece of cake! You’ve got the hang of your customized apps, super sophisticated cloud-based CRM and even the reporting tools. And after months of confusion, stress-sweat and heart-stopping errors, you are finally in the know and on top of your cloud. Or so you thought. Technology is a moving target (get used to it) and it’s time to hit a new learning curve on the next frontier—Big Data.

Business intelligence commandos and consultants all over the world are set to help companies harness the power of the massive amounts of unused information they are unknowingly collecting in an effort to bring business decision making to the next level. But first you have to understand what the heck it is.

Big Data: A big fancy definition

If you’ve been searching online for a Big Data definition, chances are things are more confusing than ever. Try picturing outer space: it’s vast, complex, unstructured and totally chaotic—unless you know what you’re looking for. Still confused?

The good people at Gartner have crated an understandable definition of Big Data describing it as “high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making”. Big Data is about identifying changes and relationships and linking data that move at different speeds rather than focusing structured, predetermined variables at regular intervals. This includes embedded text as well as various data types and locations all for the purpose of establishing communication patterns and links among otherwise exclusive groups.

So what does it look like, exactly?

Big Data is commonly understood to be unstructured data, is sourced from text files and accounts for about three quarters of an organization’s total data. It’s often measured in petabytes or exabytes (fancy words for really, really big) but does not refer to a specific number per se. In fact, data sets are so large and so pervasive they defy the usual methods of management and analysis. Capturing, categorizing, storing and understanding it requires construction of data-centric architectures and cloud-based APIs and machine learning algorithms to translate data into meaningful trends and identifiers.

What is it good for?

When businesses engage their customers with rewards or points systems, offer warranties or special offers, there is more to the story than just hashtags, replies and rate of usage trends. Super analysts who find trends and usable information not otherwise available within a company’s structured in-house databases tap the contents of customer feedback and communication in social media and other online sources.

Big Data can also support government and service providers in finding solutions during outages and even disasters. Searching secondary communication channels for spikes in social media keyword use or locations can reveal details that are not evident in primary communication data like direct calls or emails.

Essentially, patterns are everywhere. Everything consumers and business do leaves a massive trail of chaotic and seemingly unrelated information just waiting to be analyzed.