Few businesses by now haven’t heard of the phenomenon of big data analytics.
In fact, any discussion of big data is bound to include the numerous benefits companies stand to gain from employing big data solutions.
The use cases are certainly real, which has lead to the increased interest in big data and all its related factors.
Perhaps your business is also thinking of getting in the big data game.
But as with any trend, misinformation tends to run rampant, especially when it comes to advanced technologies.
While many big data myths have been addressed, a number seem to be stubbornly hanging onto the public consciousness, refusing to let go and remaining a prevalent fixture of the big data landscape.
These are myths that simply don’t die no matter how untrue they may be. The best that can be done is getting the correct information out there and hoping people learn why the myths are wrong.
Related Article: Go Big or Go Home: How to Utilize Big Data for Human Resources
1. You Need the Perfect Data Scientist
In an ideal world, you’ll be able to find the perfect data scientist with all the qualifications to meet your big data needs.
A perfect data scientist includes expertise in math, computer programmings, statistics, business, and more.
Finding such a person (the data scientist unicorn, if you will) is extremely difficult.
There’s a significant big data skills gap, and businesses are hustling to snatch up the best data experts out there. The best bet would be to hire a data science team composed of experts in different fields.
2. You’ve Fallen Way Behind Everyone Else
You probably feel like every business is using big data except for yours. As surprising as it might sound, that’s simply not true. Big data adoption rates have been low for a while.
A recent report shows that only 17 percent of organizations are actively using big data today. Most companies are actually only in the planning and investment stages.
So don’t feel like you’ve fallen behind. That doesn’t mean you shouldn’t at get started on the big data path, but rushing into it is bound to be more costly than taking the calm, patient approach.
Related Article: Big Data: One Key to the Success Behind the Marvel Movies
3. You’ll Get Guaranteed Answers
The conventional thinking goes that with more data comes more certainty along with concrete answers. But that view is evidence of a fundamental misunderstanding of what big data is.
Even though more data can be a benefit, ambiguity still exists no matter how much information you have. Diverse data can likewise paint a diverse picture that points in multiple different directions at once.
What all this means is that big data can certainly act like a guide, but it doesn’t provide the guaranteed answers businesses often want. Human judgment and decision making is still needed to reach the correct insights.
4. You Can’t Use It as a Small Business
One prevailing thought is that big data is only for big business, that only the larger companies have the resources, personnel, and technology to properly use is.
This thinking discounts the various advanced big data technology has taken in recent years, opening up the strategy to smaller organizations.
Big data analytics tools, for example, have become more affordable and easier to use, while overall costs have gone down.
Even small businesses can gain a lot from utilizing big data, and the shouldn’t be too intimidated to do so.
5. You Can’t Use It for Every Problem
In much the same way big data doesn’t guarantee an answer, it also can’t be used for every business problem you come across. Too many companies look at big data as a secret ingredient needed to overcome every challenge.
It can be helpful, even pivotal, in certain situations, but not for every dilemma.
Related Article: The Skinny on Big Data: Everything You Need to Know From Our CTO
There are simply some problems which big data can’t be used for. Trying to shoehorn it into every process and operation will just make things messier than they have to be.
Big data has a lot to offer, but it’s best used when it’s properly understood.
The first step toward understanding it is ridding yourself of the wrong ideas.
The above myths remain ingrained in many businesses’ perceptions of big data.
Hopefully learning why they’re myths will help you implement your big data solutions correctly the first time.