Big Data Myths

Everybody seems to be talking about Big Data. But what does it really mean? We at Pitney Bowes believe that there are several common misconceptions that can cloud business executives’ understanding of Big Data and impede their ability to discern what is relevant in the sea of information. Big Data Myths-

Big data myths include:

  1. Consumers want to share data with brands in return for better content and offers
  2. If I am not collecting it, it’s not important
  3. I have a lot of data, but don’t do anything with it
  4. More data is always better than less data
  5. Technology will handle everything for us
  6. My company has no use for Big Data analytics  
  7. Big Data is about volume
  8. Big Data is only for the IT department
  9. Big Data is trending and will go away soon
  10. Insight comes from data analysis 
  11. Big Data requires a lot of money to implement

We decided to put our own twist on these myths and with the help of data visualization, present them in an infographic format. We believe this format will help you understand what Big Data is all about and how it can be used to transform your business.

“Big Data” myth 1: Consumers want to share data with brands in return for better content and offers

Many brands think “if I give consumers more personalized content and offers, they’ll be happy to share their data”. It’s an appealing idea that revolves around the premise that people care about privacy less than they care about value. Who wouldn’t want to get more relevant information about the things she likes? The problem is, this approach doesn’t take into account consumer psychology. 

There are three key reasons why this strategy fails: 

1) Brands don’t understand

Our view of Big Data analysis includes understanding that, despite its name, it is not about big volumes of data; it’s really about using data in new ways. It’s not just looking at how to connect the dots, but also finding new dots – ones you never thought would be important until you are able to explore what else they may reveal. 

Brands need to conduct the analysis and find new opportunities. Based on our own experiences, we have found that brands are just not very good at understanding what is actually relevant. This leads to a lot of wasted investments and time as marketers try to find the golden needle in the Big Data haystack; we end up with more data than we can process, and not enough insight on how to use it effectively.

When consumers share information, they need confidence that brands really understand why their data is important and how it will be used. Consumers also want brands to explain what they’re going to do with the data; otherwise, they feel like their personal info isn’t safe or secure.  

2) Brands don’t know what consumers want

We believe that companies need a better approach for dealing with consumer-data sharing: start by asking people. People do care about receiving offers tailored to their tastes, but they also want to be sure that the information collected about them is secure. They are increasingly wary of giving up their data if it means they have to give up control over how it is used. 

When consumers are asked what they want in exchange for sharing their data, they are more likely to share. Companies need to think beyond coupons and discounts; people value knowing that brands understand what’s important to them, not just getting offers about things they’re interested in buying anyway. This can lead marketers on a path toward better-informed decisions and ultimately higher return on marketing spends. 

3) Brands don’t do enough with the data once collected

It’s never just about “do you collect it or not?” It’s about how you use it. Just because you’re able to collect data doesn’t mean that you can actually do anything with it. When consumers are asked what they want in return for sharing their data, the things they ask for are often very specific, practical requests. They want brands to contact them before sending coupons so they’ll be sure to read them. Or they want brands to tell them when offers will expire, so they know whether or not to act on them. 

Huge information in the strict sense implies enormous volume of organized and unstructured information. That’s true. Presently, what isn’t? How about we expose a few major information legends.

Organizations manage a bounty of information consistently and the volume of information being made and put away is a steadily expanding peculiarity, which needs examination and investigation. This is the place where the idea of huge information examination comes in.

Enormous information utilizes items from a bunch of crude information and recognizes connections to acquire new bits of knowledge and make expectations about what’s to come. The crude arrangement of information is utilized to construct models, run reenactments and adjust information focuses to perceive what every modification means for the subsequent data/understanding and forecast. This has been embraced by associations to help with brilliant and more educated choices.

With its taking off prevalence, a couple of significant misguided judgments have obscured the usefulness of large information. A couple of these fantasies will be exposed as a feature of this article. A useful tidbit: ‘less analysis, more receptiveness’ is what the world requirements a greater amount of!

Given the volume of large information produced consistently from various sources like sound, video, and pictures, it can get somewhat filthy! Huge information has been acquainted with make manual cycles programmed, subsequently lessening complexities of taking care of this information.

Large information investigation utilizes various advances and recreation apparatuses that might appear to be too huge to even consider dealing with from the outset, however so did mobile phones and PCs! All developments required a thorough learning process before it turned out to be not difficult to work and utilize.

It’s similar case for huge information devices. A couple of specific apparatuses are utilized to store, process, examine and envision informative items, which require a couple of instructional courses to become acclimated to.

Have a specialist assist you with this information, information advancements and how to approach becoming accustomed to them. The specialized system for enormous information isn’t however perplexing and intricate as it seems to be asserted or thought to be! Envision how you could manage such information whenever you have become the best at large information. This ought to be inspiration enough, correct?

Hacking has tested various information assurance benefits and has worked up an uproar among the people who uncertainty cloud innovation. All things considered, there is a need to get through this confusion that the cloud is hazardous.

This isn’t totally obvious on the grounds that, with each significant information hack, there is a consistent overhaul on safety efforts and conventions to guarantee the insurance of touchy information.

Cloud security administrations have become more rigid, and cloud sellers routinely perform programming and equipment refreshes, guaranteeing information assurance and limitation to outsider approval against all possible dangers. Reviews have become typical to keep the cloud administrations shielded from a wide range of safety breaks.


Now you see how these articles about different big data “myths” are placed on different sites, but all seem to be created by the same person compiling different articles, without much effort to make them look like they were written by different people.