Summary: Big data is surrounded with so much hype, the misconceptions often get confused for facts. How can business leaders separate big data myths from reality? In this article, we identify some of the biggest myths surrounding big data, and explain why they’re false.
One of the biggest trends over the last few years, the concept of big data is surrounded with hype. Everywhere you look, there’s someone touting a new way to capitalize on big data. There’s some new article explaining how big data will change business.
Now, don’t get me wrong. I’m not saying that big data is just hype. Quite the opposite. Data volumes are growing, and will continue to do so. This ‘big data’ offers plenty of advantages to businesses of all types and sizes. It’s a trend that you can’t ignore.
However, the problem with an overly hyped topic (like big data), is the fact that not every bit of information surrounding it is true. Misconceptions get mixed in with fact. After a while, businesses start believing these myths.
Today, let’s explore some of these common misconceptions, and explain why they’re false. Here are 5 of the most common myths surrounding big data.
1. We don’t/won’t have Big Data
If you’re like most companies, you don’t generate terabytes of data. So, you can safely ignore the idea of “big data” altogether…right?
Not so fast. The idea that you can just ignore big data altogether is one of the most common myths out there.
Here are two reasons why you can’t ignore it. First, as explained in this article, all businesses have access to more data than they realize. Just because you don’t generate “big data” doesn’t mean you can’t access (and capitalize) on it.
Second, consider the recent trends. Over the last few years, we’ve seen data volumes explode–and this trend isn’t slowing down any time soon. It’s estimated that data volumes will rise 50x by 2020. While you may not have big data now, who’s to say you won’t have it in the near future? Wouldn’t you rather get ahead of the trend now, before you’re stuck playing catch-up?
“Many non IT related companies feel that they don’t have Big Data and hence conclude that they don’t have to deal with it (Ostrich hiding itself with its head in the sand),” says Dj Das, Founder & CEO of Third Eye Consulting Services & Solutions, LLC. “The truth is that, the rate at which Data is growing in every field, every domain, everyone would have to deal with the data deluge one day or the other. The earlier someone can get their arms around it, understand how to deal with it and make best use of Data for business decisions, the sooner they will be prepared for the future.”
2. Big Data is only an IT problem
Many make the mistake of assuming that big data is all about technology. The “big data project” starts in the IT department. They get all the technology in place before exploring ways it will benefit their business.
In reality, it should be the other way around.
Big data is not a technology project. It’s a business project. You must first figure out what business problem you want to solve before exploring the technology. Of course, the IT department will be involved implementing the technology. But, it must stem from a business need if you want it to succeed.
“Most engineers are of the view that non-tech senior management somehow expect the IT teams to create magic by using the “Big Data” trick,” says Binny Mathews, Co-founder of DeZyre. “However for Big Data to be effective it needs buy in from various teams including senior management and domain teams like marketing, finance etc.”
3. Big data are always correct
George Burns once said, “If you live to be one hundred, you’ve got it made. Very few people die past that age.”
Statistically speaking, he’s correct. But if you take the data at face value, you’d be wrong.
I share that quote to make a point. Big data has something of a “magical” feel to it. Somehow, it pulls answers out of overwhelming amounts of data. Because there’s so much data, you can’t possibly go through and verify that everything is correct.
So, should you just have to assume it’s accurate? Can you blindly take that data at face value? Not so fast.
That’s when problems occur. If you don’t understand your data, or the process of gathering/refining that data, you will draw inaccurate conclusions.
Just like regular data, big data’s effectiveness depends on multiple areas. As explained below, the accuracy of the answers you draw from big data depend largely on four important factors.
“In learning about the space, one of the most striking myths is that “big data” hold the unequivocal answer – that ‘big data are right,’” says Dave Crusoe, Director of Technology & Academic Success, Boys & Girls Clubs of America. “In fact, “big data” are prone to a variety of conceptions and misconceptions that can serve to reinforce preexisting stereotypes or behaviors. What we gain from “big data”, in turns, is only as good as (a) the accuracy of the sources for data; (b) the interrelationship of the data, or the assumptions that play into the interrelationship; (c) the assumptions that are used to analyze the data and (d) the coarse generalizations that are used to make sense, and act upon, the data. Errors and assumptions are injected all along that activity chain.”
“So, the key take-away is that although “big data” can provide insight about all sorts of behaviors, they can only do so at a coarse, rough level. In fact, the insights that “big data” provide are only as good as the effort that went into understanding it, and even those are limited at best. “Big data” provides a signal, but not the answer; the answer, instead, must come from the synthesis of a variety of sources, “big data” and otherwise.”
4. Big Data will solve almost any business problem
Over the last few years, big data has been touted as the solution to many different problems. For instance, it’s presented as a way to get more customers, reduce churn rate, improve employee satisfaction, and so much more.
The problem is, it’s turned into something of a ‘catch-all’ business solution. As a result, many businesses hold unrealistic expectations for big data.
Can big data answer important questions for your business? Of course. Will it solve every problem you have? Of course not.
Big data isn’t a magical solution that will automatically provide business insights. It helps different businesses in different ways. What’s the key? As explained below, if you want big data to provide the right answers, you must first ask the right questions.
“One of the biggest myths about big data is that it can solve almost any business problem,” says David Ferguson, CEO & Founder, 5000fish, Inc. “The reality is that generally the answers you get from analyzing big data is only as good as the quality of the data being analyzed (junk in – junk out) and if you happen to be asking the right question (which is more difficult than it sounds). Companies that buy into the “magic 8-ball” of big data analysis tend to quickly realize that the hype around big data also means big cost to their bottom line.”
5. Everyone else is way ahead of you in big data adoption
Based on the hype surrounding the topic, you’d think that everyone has already jumped on board. You’d think that businesses across the globe are pulling insights from their next-gen big data analytical platforms as we speak.
The reality: According to a recent survey, 17% of companies use big data in their organization today.
Now, does that mean you should ignore it all together? Does that mean it can’t help your business? Of course not.
Rather, view it as an opportunity. Businesses get discouraged because they feel they’re falling behind. But, that’s just not accurate. Don’t assume you’re getting left in the dust. Many organizations are still warming up to the concept. They’re in data-gathering mode, but they haven’t figured out how to turn this data into actionable insight.
“According to Ginni Rometty, CEO of IBM, Big Data is the ‘next oil’,” says Tom Smith, Research Analyst at dzone. “However several executives pointed out that this is unrefined oil for the next 10 to 20 years. The future of Big Data is providing real-time data to connect people, machines, experiences, and environments in a way to improve life experiences in a more personal way – from fewer traffic jams to better quality of life throughout life.
However, there are very few companies really doing Big Data right now because there’s so much data in repositories that the next challenge is to figure out how to aggregate the data so it can be analyzed. We also need to figure out the right questions to ask to transform business and the customer experience. Companies with sufficient talent are already doing these things for their clients; however, they see many more possibilities as more people learn how to prepare and analyze data across disparate databases.”
While this list could certainly go on, the points listed above are just a few of the common myths surrounding big data. What do you think? Would you add anything to the list? If so, please feel free to share in the comments.
8 thoughts on “5 common big data myths”
With the explosion of big data, companies are faced with data challenges in three different areas. First, you know the type of results you want from your data but it’s computationally difficult to obtain. Second, you know the questions to ask but struggle with the answers and need to do data mining to help find those answers. And third is in the area of data exploration where you need to reveal the unknowns and look through the data for patterns and hidden relationships. The open source HPCC Systems big data processing platform can help companies with these challenges by deriving insights from massive data sets quickly and simply. Designed by data scientists, it is a complete integrated solution from data ingestion and data processing to data delivery. Their built-in Machine Learning Library and Matrix processing algorithms can assist with business intelligence and predictive analytics. More at http://hpccsystems.com
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Great Article, Thank you for clear some doubts about BIG DATA.
* Other Than IT Fields can use it also
* No need to high Budget in all the case
* It will tell you what will happen next
* Don’t care if Everybody is doing
* All about size
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