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Understanding The Relationship Between Big Data and the Cloud

In today’s IT environment, do you know what the buzzword is? For both customers and service providers, it is the most crucial factor.

The keyword ranking on Google these days is “data.” There is a wealth of information available both online and offline. At least 8 out of 10 – and occasionally 10 out of 10 – of the things we use daily generate data.

For instance, the data generated over social media accounts, cell phones, images, communication, services, gadgets, credit cards, enterprises, and cars are the primary resources. Understanding how much data humans generate isn’t enough. So, let’s look at some stats to put things in context and see just how much data we’re leaving behind with every click and login.

According to Domo, in 2024, each individual will create 2 MB of data per second. We generate 3.5 quintillion bytes of data each day on average.

That’s a tremendous amount. It starts with one digit and ends with 18 zeroes.

This is referred to as “big data.” However, data without context is simply that: data. This jumble of numbers, figures, and decimals is useless unless it can be processed to extract valuable data or used to improve people’s service delivery.

Computation, computations, and analytics must convert this data into something meaningful. To better comprehend the link between big data and cloud computing, first define both phrases.

The Big Data

Big data is a term that refers to a large amount of data generated by various actions conducted online and on other electronic devices.

It is data, for example, when you search for something on Google. Data is everything you do on an electronic device: the messages you send on WhatsApp, the emails you get on Gmail, the food you purchase on DoorDash, the tasks you ask Alexa to do, etc.

At the time of writing, we reached out to industry experts. During our survey, one of the SmashCloud experts suggested Data in itself is of no use or significance except for it should be transformed into something valuable to extract Information. Hence, you can state that Value! is the main V of all the 5Vs.

The referred main characteristics (V5) of big data are listed below:

  •         Volume: The amount of data produced from various sources is volume.
  •         Variety: It denotes the wide range of data sources from which data is derived.
  •         Velocity: It is a unit of measurement for the rate at which data is generated.
  •         Veracity: Veracity is a term that describes the quality of data collected and gauges its correctness.
  •         Value: It displays the importance of analyzed data.

We’re not talking about MBs or even GBs of data when we talk about extensive data. We’re talking about quintillions of bytes and more. So, here’s the issue: such a large volume of data can’t be handled and examined on standard computers.

To analyze this data, you’ll need a lot of storage, machines that can perform complicated computations quickly, and resources to show it to be utilized for anything.

Centralized storage with limited computing power can work for traditional data but not for big data. As a result, cloud computing offers a solution to this issue.

The Cloud Server Or Cloud Computing

As we all know, a cloud is something that does not have a physical presence, at least not in our world. Cloud computing refers to on-demand computing resources and platforms that allow users to access a wide range of services without relying on local resources.

Take cloud storage, for example. Our information is saved on decentralized servers located in different parts of the world. We don’t have to maintain these servers to keep data; someone else does it for us, and all we have to do is upload it.

There are three types of cloud computing services:

1. Software As A Service (SaaS)

  •         SaaS provides customers with a variety of application software that they may use without installing anything on their computers.
  •         The user is not responsible for the software’s operation and must adjust parameters to suit their needs.
  •         SaaS applications include Dropbox, Salesforce, and Google.

2. Infrastructure As A Service (IaaS)

  •   Infrastructure as a Service (IaaS) is a type of cloud that offers consumers diverse infrastructure assistance, except that the infrastructure does not exist in physical form.
  •  Through virtualization, all services such as hardware, software, servers, storage, and other infrastructure are delivered by a third party in the IaaS model.
  •  Linode, Amazon Web Services, and Microsoft Azure are all examples of IaaS.

3. Platform As A Service (PaaS)

  • Software as a Service (SaaS) provides a framework for developers to leverage to construct and create apps.
  • Third-party service providers handle all of the platform’s work, while developers are in charge of their apps.
  • AWS Elastic Beanstalk, Heroku, and Force.com are all examples of PaaS.

The Relationship Between Two…

Big data is typically too massive and complex for ordinary computers to handle. Big data would be worthless without cloud computing because data lying idle is worthless.

Cloud computing allows us to make the entire process of studying extensive data more time efficient and less time demanding. Don’t believe this is a one-way street; cloud computing is also essential because of big data.

If big data vanishes, the number of cloud-based apps will dwindle dramatically naturally since they would have lost their importance. As a result, big data may be considered to support the development of cloud computing services.

Final Words

Data storage has become inexpensive and straightforward, thanks to cloud computing. We are witnessing a shift in how data is managed and stored as a result of decentralized storage. It has become easier for remote teams to collaborate on projects that need cooperation since information is accessible everywhere at any time.

The interruptions created by the coronavirus epidemic have increased the relevance of cloud computing even more. People are accessing data and managing their job remotely now that work-from-home is being introduced all around the world.

Cloud computing’s popularity and demand will only grow in the future. The extent to which cloud computing is applicable will be determined by how well it handles requests while adhering to tight security procedures for adequately storing and transferring data.

Also Read: Computer Science vs Software Engineering: Quick Guide

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