Big Data Myths

Busting Three of the Biggest Myths about Big Data

Separate fact from fiction as we dispel some of the nastier and more persistent myths surrounding big data and how it is being used by brands.

The words “big data” have been popping up in the media for a few years now, so we understand if you feel a bit tired of hearing them over and over. Big data is a powerful approach to business learning that can help you make decisions in ways that no other solution can. In an effort to dispel any misconceptions or outright untruths surrounding big data, here are some of the most common myths and why they are just plain wrong:

Myth #1: Big Data is a Waste of Money

Like any tool, the value you get out of big data depends on how you use it. Yes, buying a fleet of servers and strapping them to Hadoop may not be the answer to your company’s ails, but third party data warehousing and analytics can actually be an agile solution with a price point scaled to your needs.

Secondly, big data when used appropriately can actually help you leverage other systems to make smarter decisions and get higher ROI. Imagine strapping data-enabled targeting to your programmatic buys using years’ worth of information on millions of customers’ behavior. The ability to waste less money on ad buys that don’t reach your target is just one example of how big data can actually put money back in your pocket.

Myth #2: Big Data Is the Same Thing as Analytics, Which We Already Do

Small-scale analytics are great at highlighting behaviors over a short period of time, but it cannot yield patterns that create true insights. Big data’s ability to amass several data sources including third-party data can create correlative overlays, accurate benchmarks and predictive capabilities that could never come from one limited source alone. The difference is akin to having a single shot glass of water to quench your family’s thirst or a whole well in your backyard.

Myth #3: Big Data Is Creepy

Once again, big data is a tool that can be wielded in different ways. Attribution is one such way, and while its capabilities are potent for marketing, it may give average consumers the shivers. Advertisers know this, so most data tracking over multiple sites requires an opt-in.

Other uses of big data have little to do with “spying” on people since only anonymized data is used. Big data also frequently applies to things that have nothing to do with people at all, like weather patterns and crop yields.

While adoption of big data is already widespread, these sort of myths will persist unless key decision-makers educate themselves more about big data analytics and its true potential. Those who prefer to accept rumor at face value are doing their organization a real disservice. Perform the research needed to determine how big data can empower your organization and leverage the knowledge it retains. Big data is not an intrusion, but rather the direction that all computing is moving towards.

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