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10 undeniable reasons people hate Big Data

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6 June 2014


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10 undeniable reasons people hate Big Data

I love you, I hate you

Big data isn’t going anywhere, so—much like an arranged marriage—it’s best to learn to love it. It’s no surprise that a number of people, particularly business owners, hate big data. However, that’s not going to make it go away or make it any less paramount to business. Instead of digging in your heels and refusing to give it an honest shot, it’s time to give it a fair run.

Here are the 10 biggest reasons people (fairly) hate big data and what to do about it. Maybe the issues aren’t quite as reasonable as they appear.

1. Big Data is confusing.

It certainly can be if you don’t know what you’re looking for, how to gather it, how to organize it or how to analyze. If a non-profit serving the African American community’s health needs conducts a study on their target demographics exercise and eating habits, what’s next? Big data is completely useless if it’s not used properly.

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2. Big Data is impossible to keep accurate.

The reality is that big data is never 100 percent accurate. People lie on surveys, they get things wrong by mistake, and nobody wants to admit to some data survey questions like how often they really eat at McDonald’s. Keep in mind that big data isn’t supposed to be flawless, but rather showcase trends and habits.

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3. Big Data is a beast to organize.

Yes, it is, assuming you don’t have the right software and staff to make it happen. There’s a variety of CRM software available, and you can find something to fit into any budget. Don’t assume that the costly Raiser’s Edge is the only option or that your admin staff won’t be able to master the free software you scored. Choose software that works for you, and don’t let finances be the only driving factor.

4. Big Data is always changing.

This is also true, which is why it’s important to organize and analyze it right away. With some data, if it sits on the figurative shelf collecting dust for even a month, it’s already outdated. Collecting big data is an ongoing process, not a one and done task.

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5. Big Data doesn’t mesh with action.

It should if you’re doing it right. When collecting data, make sure you have a plan of action in mind. If you use the right tools, such as the Ensighten data layer, you’re able to collect customer data from every digital touchpoint, own all the data as first-party to your business and you can act on data in real-time to deliver personalized user experiences across every device and channel.  You must be able to act on the data.

6. Big Data takes too much manpower.

This is only true if you choose a collection approach that doesn’t click with your capabilities. If you’re collecting handwritten surveys from 10,000 people, then yes, it takes too much manpower. Utilize technology and make your life easier.

7. Big Data is expensive to buy.

There are many ways to get big data, and some of them cost a pretty penny. If it’s out of your budget, choose a different option or undertake a survey yourself. There will always be luxuries in life, but that doesn’t mean you have to indulge in them.

8. Big Data is not useful to me.

If it’s not useful to you, you’re either considering the wrong data or don’t know how to analyze it. Not all big data is going to be helpful to every business. That should be one of the core factors when deciding which data to analyze.

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9. Big Data is not what my funders want to see.

If you’re required to include data and statistics as part of a grant proposal or for a potential angel investor, then make sure the information you provide is exactly what they want. If one set of data doesn’t provide it, find another. They say you can find research to support absolutely any theory, so consider it a treasure hunt.

10. Big Data is too vague.

If you’re looking at something like Census Bureau surveys to link flower shopping habits in Baltimore, then yes, that information is too vague. Depending on how niche your needs are, this might be something you need to cultivate yourself.

Remember that big data is a series of tools, and they’re not all going to help build your project. Make sure you’re collecting all of the data that you can, and when choosing the right tools, choose wisely, though, as it’s like being gifted a chainsaw to level a forest when all you had before was a hack saw.


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