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Difference Between Big Data and Machine Learning


We live in the richest and highly advanced period in human history. Our modern civilization has already surpassed some predictions from science-fiction authors. Watching interviews where Isaac Asimov predicts services like YouTube and FB force our spines to shiver. If you say that you have access to a library of collective human knowledge and the ability to communicate with people worldwide at your fingertips, the average US citizen would consider you a madman. 

So, it is not surprising that modern people get overwhelmed with new technologies. In this article, we want to tell the difference between Big Data and Machine Learning to help avoid confusion at least in this complex field of knowledge.

What is Big Data?

Big data are formidable volumes of data that cannot be efficiently processed by traditional systems and Big Data analytics is the process of collecting and analyzing these data volumes (which, most commonly, concern human user behavior online or in terms of a certain interactive system). The primary goal of this process is to get a clear picture of current trends and predict future shifts in user behavior. Governments and private companies from all over the world are looking for hidden patterns. 

This information allows them to have a cohesive image of trends and conduct their actions in accordance with it. However, private businesses are the primary users of big data. Having the proper information allows companies to understand the markets and have an edge over their competitors. 

What is Machine learning (ML)?

The majority of computers work according to patterns that programmers have coded into them. ML is here to change that. This technology allows computers to conduct individual research and learn by themselves. Machines have more computing power than humans, allowing them to analyze huge chunks of information in a matter of seconds. This technology opens the possibility to create autopiloting cars or self-sufficient Artificial Intelligence.   

What Differentiates Big Data from Machine Learning? 

It is essential to remember that both big data and machine learning are the products of data science. Some people confuse them with each other. Yes, you can use Big Data and Machine Learning in a single system. However, these are entirely different technologies and there is a difference between machine learning engineers and data scientists.

Let’s take a look into the unique features that are separating these technologies from each other: 

  1. During the process of collecting and understanding raw data, the analytics use various tools. This software helps humans to analyze information and make rational decisions quickly. On the other hand, ML (Machine Learning) frees computers from following the encoded instructions, learning, and creating new solutions by themselves.
  2. The main work of big data analytics is to find hidden patterns in vast chunks of information. Computers conduct such things by analyzing the previous data and making the decision according to available data. In comparison, Machine learning is helping machines to react to unknown inputs.
  3. The main goal of big data is to get the raw information out of different platforms and search engines. After that, you can entrust a computer, powered by ML, to analyze the data and give predictions about future tendencies. 
  4. Machine Learning is freeing people from doing monotonous work over and over again. At the same time, the main goal of big data is to analyze the information of human behavior and find patterns.

What is the Future of Big Data and Machine Learning Techs? 

According to DATAREPORTAL, we had almost half a billion new social media users, and 1.3 billion dollars was spent on online shopping in 2021. 4.66 billion people, or 59.5% of the worldwide human population, are connected to the global web. Additionally, more than 60% of humans possess smartphones and can generate information. Our team was shocked when we found out about these numbers.

Modern technologies are only scrambling the surface of information produced by human civilization. We need to stop focusing on the differences between big data and machine learning and start considering how to combine these powerful technologies to profit in our fast-paced world. Our team is encouraging you to implement big data and machine learning into your everyday work. This tech will not only make your work more efficient but will help you to embrace future trends.