The National Institute of Standards and Technology defines five essential characteristics:

• On-demand self-service: You can provision things such as servers and storage as needed and without interacting with someone.
• Broad network access: Your cloud resources are accessible over the internet (if enabled) by various methods, such as web browser or mobile phone.
• Resource pooling: Cloud providers pool their servers and storage capacity across many customers using a multi-tenant model. Resources, both physical and virtual, are dynamically assigned and reassigned as needed. The specific location of resources is unknown and generally unimportant.
• Rapid elasticity: Your resources can be elastically created and destroyed. This can happen automatically as needed to meet demand. You can scale out rapidly. You can also contract rapidly. The supply of resources is effectively unlimited from your viewpoint.
• Measured service: The resource usage is monitored, controlled, and reported by the cloud provider. You have access to the same information, providing transparency to your utilization. Cloud systems continuously optimize resources automatically.

There is a notion of private clouds that exist on the premises or that arecustom built by a third party for a specific organization. For our concerns, we will be discussing public clouds only. By and large, most analytics will be done on public clouds, so we will concentrate our efforts there.

The capacity available at your fingertips on the public clouds is staggering. AWS, in June 2016, had an estimated 1.3 million servers online. These servers were thought to be three times more efficient than enterprise systems.

Cloud providers own the hardware and maintain the network and systems required for the available services. You just have to provision what you need to use, typically through a web application.

Providers offer different levels of abstraction. They offer lower-level servers and storage where you have fine-grained control. They also offer managed services that handle the provisioning of servers, networking, and storage for you. These are used in conjunction with each other without much distinction between the two.

Hardware failures are handled automatically. Resources are transferred to new hardware and brought back online. The physical components become unimportant when you design for the cloud, it is abstracted away, and you can focus on resource needs.

The advantages of using the cloud are:

• Speed: You can bring cloud resources online in minutes.
• Agility: The ability to quickly create and destroy resources leads to ease of experimentation. This increases the agility of analytics organizations.
• Variety of services: Cloud providers have many services available to support analytics workflows that can be deployed within minutes. These services manage hardware and storage needs for you.
• Global reach: You can extend the reach of analytics to the other side of the world with a few clicks.
• Cost control: You only pay for the resources you need at the time you need them. You can do more for less.

To get an idea of the power that is at your fingertips, here is an architectural diagram of something NASA built on AWS as part of an outreach program to school children:

When given voice commands, it will communicate with a Mars rover replica to retrieve IoT data, such as temperature readings. The process includes voice recognition, natural speech generation from text, data storage and processing, interaction with an IoT device, networking, security, and the ability to send text messages. This was not a years' worth of development effort, it was built by tying together cloud-based services already in place.

And it is not just for well funded government agencies such as NASA. All of these services and many more are available to you today if your analytics runs in the cloud.