What Is Cloud Computing?

Modern data science can’t exist without the cloud, so it’s important to familiarize yourself with what cloud computing is and how it works. Understanding the cloud in the context of data science will help you see how these different technologies work together in your future profession. Learn the answer to the question, “What is cloud computing?” below and discover the benefits of enrolling in one of The Data Incubator’s renowned data science programs. 

Cloud Computing Definition

What is cloud computing, exactly? Simply put, it’s the delivery of IT resources over the internet. Those resources are computing services such as:

  • Servers
  • Software
  • Storage
  • Networking
  • Databases

Instead of keeping resources like a server on their premises, a business accesses resources in a virtualized environment (the cloud) and pays a company (a cloud service provider, or CSP) every month for the privilege. The great thing about cloud computing is that it’s on-demand. That means businesses only pay for the services they need and can scale resources up and down as required.  

So what does any of this have to do with data science? As a data scientist, you’ll be dealing with enormous data sets that must be kept somewhere. Your future employer will probably use cloud computing to scale and secure their data. So you’ll likely be analyzing data that is stored in the cloud

Did you know the term “cloud” entered widespread use when Amazon launched its Elastic Compute Cloud (EC2) in 2006?

TDI’s Data Science Bootcamp and Data Science Essentials help you hone the skills needed for a future career as a data scientist. In both programs, you’ll solve real-world data problems under the supervision of world-class instructors. Learn more about TDI’s data science programs.

How Does Cloud Computing Work?

As you’ll be working with data stored in the cloud, it’s important to know how this technology operates. The specific functionality of cloud computing, though, depends on the deployment model.

Private Cloud

A private cloud belongs to a single business, which has control over all of its computing resources. The business can customize cloud architecture, create tailor-made security protocols and scale resources whenever they like. A CSP often hosts the resources required for a private cloud off-site.

Public Cloud

A business will need to share resources with other users in the public cloud model, resulting in less control. A CSP will take care of security, scalability and other factors on behalf of the business. 

Hybrid Cloud

A hybrid cloud combines private and public deployment models. A business will share some resources, such as networking, with other users in a public cloud and keep other resources, such as software, in a private cloud. 

The Benefits of Cloud Computing

Here are some of the advantages of cloud computing:

Cost Savings

Businesses can save costs when virtualizing resources in the cloud rather than keeping them in-house. This eliminates the need to purchase expensive physical servers and networking equipment.


It’s easy for businesses to scale computing resources up and down in the cloud. There are no physical restrictions like with on-premise IT set-ups. 

Data Analysis

It can be difficult to perform data analysis without cloud computing. The cloud lets you access data from any location in the world, making it easier to do your job as a data scientist. 

The Drawbacks of Cloud Computing

There are also disadvantages of cloud computing:

  • While companies can save money by virtualizing resources, they need to pay CSPs monthly fees for their services. 
  • Storing data virtually can increase the risk of a data breach or other cybersecurity events.
  • The cloud can experience network downtime and outages like other IT setups. 

What are you waiting for?

Your data science career starts here! Evolve into the data scientist you’ve always wanted to be with the following programs:

  • Data Science Essentials: This program is perfect for you if you want to augment your current skills and expand your experience. 
  • Data Science Bootcamp: This program provides you with an immersive, hands-on experience. It helps you learn in-demand skills so you can start your career in data science. 
  • Data engineering bootcamp: This program helps you master the skills necessary to effortlessly maintain data, design better data models, and create data infrastructures. 


We’re always here to guide you through your journey in data science. If you have any questions about the application process, consider contacting our admissions team.


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