What is Big Data?

Big Data is a type of data that is in a huge quantity and is still growing rapidly. It is so large and complex that it is impossible to manage it using the traditional ways of computing and to store it to process it effectively and efficiently. Machine Learning is used to process and understand big data as the accuracy of Machine Learning models increases if trained using such amount of information.

The process of handling Big data and training Machine Learning models is a perfect match as without enough data we can’t train models to make future based decisions because if we used a small piece of insights to train models, then it might lead to a misleading prediction about the future course of action.

The Need for Big Data

Big data plays a major role in training a machine learning model, which can be used with thousands of data points. An organization competing in a very fast-changing market will always love to train and deploy a Machine Learning model that can make predictions in just a matter of milliseconds so that the organization can make a good move as quickly as possible.

For such a competition, it is essential to analyze the good amount of information that should be considered in training models to leave a positive impact on the future outcomes of the competition.

Big data includes all types of stats, which generally include structured and unstructured, information collected from emails, social media, images, web scraping, and even machine sensors. The traditional products used as tools of Business Intelligence are not able to handle such amount of insights.

They still can be used in some internal analytics, but an organization cannot depend on such tools at this rapidly growing competition. With the introduction of cloud computing and Machine Learning, it is now possible to manage such a huge amount of information that comes in such high volume.

Big Data in Context with Machine Learning

If you are a practitioner in Machine Learning, you must know that we need the right amount of insights and statistics to be applied to our Machine Learning model. However, it is not compulsory to have big data to train a model, but training a model using it will help in improving the accuracy of our Machine Learning models.

Also, Read – Object-Oriented Programming for Machine Learning.

To conclude the need for big data, I will say that if an organization uses big data for training machine learning algorithms, the organization will always anticipate the future and be prepared for the disruption. I hope you liked this article, Feel free to ask your valuable questions in the comments section below. You can also follow me on Medium to learn every topic of Machine Learning.

Also, Read – Web Scraping to Create a CSV.

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Aman Kharwal

I am a programmer from India, and I am here to guide you with Data Science, Machine Learning, Python, and C++ for free. I hope you will learn a lot in your journey towards Coding, Machine Learning and Artificial Intelligence with me.

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