Cloud computing effect on Data Architecture [6 out of 10]

This is a?series?of articles to talk about the importance of having a solid data architecture in your business. The series will include the below articles:

1- Introduction to Data Architecture 

2- OLAP vs OLTP 

3- Data Warehouse Architecture deep dive 

4- Data Lake Architecture deep dive 

5- Data Lake vs Data Warehouse Architecture 

6- Cloud computing effect on Data Architecture [current article]

7- Rise of Data Mesh Architecture

8- Data Mesh Vs the rest

9- Rise of DeltaLake Architecture

10- Which Data Architecture shall I choose?        

What is cloud computing?

Cloud computing is a general term for anything that involves delivering hosted services over the internet. These services are divided into three main categories or types of cloud computing:

Infrastructure as a service (IaaS):

In this type of cloud computing, the cloud provider offers virtualized computing resources, such as servers, storage, and networking. Customers can use these resources to build their own IT infrastructure, including running and managing their own applications and operating systems.

Platform as a service (PaaS): ?

This type of cloud computing provides customers with a platform for developing, running, and managing their own applications without having to build and maintain the underlying infrastructure. The cloud provider offers a platform with tools, programming languages, and libraries that developers can use to build and deploy their applications.

Software as a service (SaaS):

In this type of cloud computing, the cloud provider offers a complete software application that is accessible over the internet. Customers can access the software application through a web browser or other client software without having to install or maintain any software on their own devices. Examples of SaaS applications include email, customer relationship management (CRM) software, and productivity tools.

Public and private cloud:

Cloud computing is a type of service that can be delivered either through a public or private cloud. A public cloud is available to anyone on the internet, while a private cloud is a network or data center that provides hosted services to a restricted number of users with specific access and permission settings. The primary aim of cloud computing is to offer convenient, scalable access to IT services and computing resources.

The infrastructure required for cloud computing, which includes hardware and software components, is critical for successful implementation. Cloud computing can also be referred to as on-demand or utility computing.

Cloud computing has gained popularity among individuals and businesses because of several benefits such as cost savings, enhanced productivity, improved speed and efficiency, better performance, and increased security.

Key benefits from cloud computing:

• Cloud computing is the delivery of different services through the Internet, including data storage, servers, databases, networking, and software.
• Cloud storage has grown increasingly popular among individuals who need larger storage space and for businesses seeking an efficient off-site data back-up solution.
• Cloud-based storage makes it possible to save files to a remote database and retrieve them on demand.
• Services can be both public and private—public services are provided online for a fee while private services are hosted on a network to specific clients.
• Cloud security has become an increasingly important field in IT.

Cloud computing effect on data architecture:

Cloud computing has revolutionized the storage and processing of data, providing organizations with scalability, accessibility, and cost-effectiveness. With cloud computing, businesses can streamline their software management by abstracting many of the operational complexities, such as infrastructure, networking, security, and maintenance.

This approach allows businesses to focus more on their core value proposition while removing the burden of managing ancillary IT tasks. The same benefits can be applied to data management as well, with cloud computing providing an efficient and cost-effective solution for storing and processing large amounts of data.

Cloud effect on data analytics:

In the past, most companies utilized on-premise Hadoop implementations for their business analytics needs. However, this approach often introduced operational complexities that made data management challenging. With the advent of cloud computing, traditional on-premise Hadoop implementations have become less necessary, and businesses can now take advantage of modern technologies like Amazon S3, Azure ADLS, and Google Cloud Storage.

These cloud-based services offer many of the same benefits as Hadoop but in a more cost-effective and easily maintainable manner. Additionally, many of these modern services utilize features that were initially introduced by Hadoop, making it simpler for businesses to store data in an efficient and scalable way. As such, cloud-based storage solutions have become a popular and viable alternative for many companies looking to simplify their data management needs.

Cloud Data Reference Architecture (AWS, Azure and GCP)

Microsoft Azure:

Data warehouse on Azure

Data Lake on Azure

Amazon AWS:

Data warehouse on AWS

Data Lake on AWS

Google GCP:

Data warehouse on GCP

Data Lake on GCP

In my upcoming article, I plan to explore the latest addition to the field of data architecture: Data Mesh architecture. Specifically, I will delve into the following topics:

• What is Data Mesh architecture?
• What are the motivations behind using Data Mesh architecture?
• What are the essential features of Data Mesh architecture?
• When is Data Mesh architecture appropriate to use?

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