6 Things People Seem to Get Wrong about Big Data

Perhaps one of the fascinating words in the twenty-first century is “big data.” It’s all over most tech articles, and companies are reeling to have them.

And yet, it’s also a word often subject to misinterpretation. Here are six things people may get wrong about it:

 1. Big Data Are for Customers Only

While many businesses are now collecting big data, they often focus on their leads and customers. They can also get them from their employees and applicants, and the information can be a huge help in improving their internal systems:

  • The company can determine the level of engagement of the employees. Disengagement, especially an active one, can cost them a lot of money.
  • The business can identify problems before they get worse.
  • The managers can also improve their efficiency and productivity without compromising the stress levels of their workers.
  • They can effectively match applicants to the right positions and help them narrow down the best candidates.

Collecting big data from their team need not be complicated either. It can be as simple as using online survey software companies can modify each time, according to their objectives.

 2. Collecting Big Data Is Enough

Perhaps for some, businesses are seeing big data as collectibles – displayed but never used. Worse, because they hardly look at this information, they fail to realize they are keeping outdated or redundant files. These can increase the risk of false figures later on.

Big data, no matter the size, is useful only when companies use them. Here are some ideas on how to harness them:

  • Understand the changing needs of the consumers
  • Determine underserved or unserved markets
  • Identify new consumers and their personalities
  • Pinpoint competition
  • Know the unique selling proposition
  • Measure offline and online marketing strategies
  • Improve products and services
  • Create new products and services

 3. Big Data Is Costly

At first glance, big data sounds expensive. Servers, which house all the information, can already be worth $4,000 for a mid-range type. Big companies such as Amazon likely spend at least $500,000 to millions.

Plus, businesses need to spend on the maintenance of these data. If they prefer to do everything in-house, then they pay for a department.

However, for those who harness information, they will realize that cost is only relative.

In the end, they can maximize the value of the collected information that can translate to higher profits and effective systems. One needs to look at Amazon and Google to know how powerful big data can be.

4. Big Data Is All About Forms

The easiest way to generate data is to let people sign up forms. A simple form can already contain various information, such as age, name, address, phone number, income levels, or ethnicity.

What many businesses don’t know, though, is they can also derive such information from other sources. These can include reports, third-party surveys, and even data provided by their competitors publicly.

They can also obtain qualitative (which means non-numbers) data from case studies, books, and other types of white paper.

5. Big Data Is Artificial Intelligence or Machine Learning

man working

Big data is nowhere near the meaning of artificial or machine learning, but they can still be interrelated.

Big data are just that – plenty of information. However, you can use AI or machine learning to make sense of what you collected. Take machine learning, for instance.

Machine learning is a concept wherein the machine “modifies” itself as one feeds it more data. In time, it generates more accurate information with the least possible human intervention.

In the context of big data, machine learning can streamline analytics that businesses might spend less on labor. They can also generate reports from this information fast.

Further, machines can handle bigger loads of info 24/7, so businesses can interpolate data anytime, anywhere.

6. Businesses Can Manage Big Data by Themselves

Companies can build an in-house team to manage and analyze big data, but because the process is complex, they are less likely to be capable of doing it by themselves.

They need the services of the following:

  • Cybersecurity firms that can help ensure the information is not easy to breach and to detect early signs of hacking or stealing
  • Third-party big data providers, such as survey companies
  • IT support from the manufacturers of the systems
  • Managers of data servers located outside the premises

As more people connect themselves online, companies can expect big data to grow. That’s okay as long as they can make sense of what they collected. Otherwise, their efforts might be in vain.

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