Evolution Of Web Technologies

When we talk about the word ‘evolution’, we know that evolution is a time taking process. It doesn’t happen overnight. It happens almost in everything that exists in the universe. When we talk about technology, more specifically about web technologies, evolution is also there.

Web technologies weren’t the same from start as they are today. They got evolved with time. In this article, we will be talking about Evolution of Web Technologies and different stages of evolution.

So, let’s first talk about the stages of evolution. Web technologies evolved from three different stages which we call as Web 1.0, Web 2.0 and Web 3.0. Let’s briefly talk about them one by one.

Stages Of Evolution:

Web 1.0:

Web 1.0 was the first generation of the world wide web, also referred to as the read-only web. This is where it all started from. Web 1.0 began as an information place for businesses to broadcast their information and only allowed users to search for information and read it. Simply put together, it was technology that offered web pages with no user interaction and feedback. Websites developed in this technology were only able to present content for reading purposes. Users could only search for the content and read it. Pages weren’t richly designed, did not have beautiful infographics as compared to today.

evolution-of-web-technologies

Web 2.0:

As technology evolved, websites were able to provide a richer and more interactive user experience. Web 2.0 has been used to describe this web phenomenon. Examples include social networking sites such as Facebook and MySpace, which allowed users to create their own profiles, share files and interact with each other on a larger scale. Web 2.0’s main focus was on improving user experience and user interaction. To do so, blogging came into play. Blogging made a layman a home-based Journalist. People write articles and share their ideas through blogging. Readers can give feedback to those articles.

Mostly importantly, remember this is the era of Web 2.0 and it will never be the final destination i.e. web 2.0 is also evolving. And the next stage is gonna be, Web 3.0!

evolution-of-web-technologies

Web 3.0:

Web 3.0 is the upcoming generation of the internet where websites and apps will be able to process the information in a smart human-like way through technologies like machine learning and big data.

Simply put together, web 3.0 will use Artificial Intelligence concepts to improve user experience. One of the most important aspects of web 3.0 is Semantic Web.

Let’s talk about Big Data, Machine Learning and Sematic Web.

Web-3.0

Machine Learning:

Machine Learning is an Application of Artificial Intelligence (AI) it gives devices the ability to learn from their experiences and improve their self without doing any coding.

Web 3.0 will be using machine learning to improve user experience. Machines will be made to learn from the past experience and old data patterns.

Semantic Web:

The Semantic Web is the knowledge graph formed by combining connected, Linked Data with intelligent content to facilitate machine understanding and processing of content, metadata, and other information objects at scale.

For instance, semantic web will show its importance when one will search for something on google and google will show most relevant search results i.e. you get exactly what you search for. Quite Amazing!

Big Data:

This is a concept known as the three Vs. Put simply, big data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can’t manage them. But these massive volumes of data can be used to address business problems you wouldn’t have been able to tackle before.

Three Vs  Of Big Data:

volume:

With big data, you’ll have to process high volumes of low-density, unstructured data. For some organizations, this might be tens of terabytes of data. For others, it may be hundreds of petabytes.

Here i will give you a couple of examples of exponential growth of data. The New York Stock Exchange is an example of Big Data that generates about one terabyte of new trade data per day.

The statistic shows that 500+terabytes of new data get ingested into the databases of social media site Facebook, every day. 

Variety:

With the rise of big data, data comes in new unstructured data types. Unstructured and semi-structured data types, such as text, audio, and video, require additional preprocessing to derive meaning.

Velocity:

Velocity is the fast rate at which data is received and (perhaps) acted on. Some internet-enabled smart products operate in real time or near real time and will require real-time evaluation and action.

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Written By:

Hadeed Ul Hassan

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