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Algorithms: The Backbone of Big Data Analytics!

Algorithms: The Backbone of Big Data Analytics!

Big Data has taken center stage since the time of its inception and this is the reason every industry across the globe wishes to take advantage of it. However data does not work alone, a lot of factors stand with it to make it work. One of them is the Algorithm.

Yes! Big Data could have a long-gone concept if Algorithms weren’t developed to support this idea. Intelligent algorithms do not only decode the data but analyze and provide the right output at the right time. The reason behind this fact is the complexity of Big Data which has made it hard to be deployed and operated. Algorithms solve this purpose by acting as the implementing agent in the system.

Algorithms are everywhere!

When you open Facebook and like a picture, you generate big data. When you Google something, you generate big data. When you open an e-commerce website, you generate big data. But what happens with this data afterward?

This is when Algorithms come into the picture. Whenever you like, search, or browse anything, an algorithm processes the amount of data you generate and gives you the outcome you need.

Google uses the PageRank algorithm to rank the search results which is reflected when we search any term and find the results as per their relevance. Facebook uses the EdgeRank algorithm to determine the position of a news feed on your wall.

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Ever-increasing Data

As per Mar Tech, currently, 2.7 Zettabytes of data exist in the digital universe. 

Data is emanating from every digital medium making it highly complicated for a normal system to handle it. With this huge amount of data exploding every minute, we have to depend on intelligent algorithms that can automate the entire procedure to make it simpler and accurate.

IoT being a revolutionary concept in itself is one of the driving forces behind the massive data generation which is not only going to flood the digital space but also going to require intelligent algorithms to extract important insights from them.

Automation and Customization: As driving factors

Since everything is getting automated, the need for algorithms has increased like anything. People need everything instantly in a customized manner. You make all the settings of your social media profile, banking applications, email accounts, and e-commerce websites. What do you think is acting behind all these customizations?

When you make your account in Uber, it saves your GPS location the very first time and prompts you each time you open your account to book a cab. Imagine how many customized accounts Uber handles each day. Surprising right?

Each time you open your Facebook account, you see the people it suggests saying “People You May Know”. How does Facebook do that? Algorithm!

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A new era of algorithms with Machine Learning

The process of automation does not end with applications and software but starts with Machine Learning. It’s only when you try to make a machine act like humans, you require algorithms to be fed into the machines. Machines are getting smarter as they are able to develop cognitive intelligence in them. They can’t just act as commanded, but can also make decisions by developing new algorithms on their own.

Robotics, Natural language processing, and machine learning have become the areas using and developing extensive algorithms to make machines smarter than ever before.

Big Data is still in its nascent stage, but the massive adoption of algorithms has made it a key for development. However, it will be interesting to know the ways algorithms will be influencing our lives in the coming years.

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Cohort Starts date: 10th Dec 2024
7 Months
₹85,044
Cohort Starts date: 10th Dec 2024
7 Months
₹85,044

About the Author

Technical Research Analyst - Big Data Engineering

Abhijit is a Technical Research Analyst specialising in Big Data and Azure Data Engineering. He has 4+ years of experience in the Big data domain and provides consultancy services to several Fortune 500 companies. His expertise includes breaking down highly technical concepts into easy-to-understand content.