Understanding Data architecture - Components and Characteristics

Data architecture refers to the established procedures used by an organization for the acquisition, archiving, and administration of data. Both the resources for data management and the organizational structure of data assets are described. Data that is organized properly will benefit those who require it. It consists of all the regulations, guidelines, models, and specifications necessary to maintain the organization's data.

Intending to translate business needs into data and technology requirements, the data architecture establishes the framework for a business strategy. Additionally, it controls how data is managed and moved around the organization.

In today’s article we will understand the components and characteristics of data architecture, and also look at the salaries of the various roles that come under this domain. Without any further ado, let’s get started.

Data Architecture Components

Now that we have understood data architecture, let us understand its basic components.

• Data Pipelines: This term refers to the procedure for gathering data, as well as its filtration, storage, analysis, and movement between points. The data pipelines include the complete process, including where and how data is transported after being acquired.
• Cloud Storage: The term "cloud storage" designates an off-site place where data is kept and is only accessible online.
• API: The API makes it possible for the host and a requester to communicate. Through an IP address, the connection is made. The API can provide the user with a variety of information.
• AI and machine learning models: These models offer an automated mechanism for the data architecture. Along with data gathering, labeling, etc., it is possible to make predictions and calculated conclusions.
• Data streaming: It implies a continuous data flow from source to destination and this needs to be processed for real-time analysis.
• Kubernetes: It is the platform for workloads involving the compute, networking, and storage infrastructure.
• Cloud computing: When data is examined, saved, and managed through the cloud, this process is referred to as cloud computing. The application of cloud computing offers advantages like reduced costs, safe data, and no need to manage the IT infrastructure because it is controlled by the cloud.
• Real-time analytics: This approach involves analyzing real-time data to gain insight into it. The organizations might choose based on this analysis.

Data Architecture Characteristics

After understanding the basic elements or components, we now look into the characteristics of data architecture.

1. Approach is user-driven

The capacity to deliver data to people exactly as they want is a feature of the data architecture. Decision-makers struggled to gather the necessary data since it was static compared to the past. The decision-makers can define their requirements and access them to satisfy the business objectives in the current situation, nonetheless, thanks to the availability of new data structures.

1. Created using shared data

By combining data from several organizational departments, the modern architecture requires shared data. Next, the information is gathered in one location.

1. Streamlined/Automated

It used to be a laborious process to distribute data and keep it up to date. Additionally, it took months to complete the processes. These procedures can be completed within hours when using automated technologies. Additionally, the user can access a variety of data types due to the existence of automated pipelines.

1. Led by AI

Data structure automation is done using artificial intelligence (AI) and machine learning (ML) (AI). Any quality issue may be resolved with the use of AI and ML, and incoming data is automatically organized into structures. A similar data set or analytics can be suggested by the automated system based on this.

1. Flexible

According to their needs and the data architecture, the organization may scale up or down. An administrator can solve issues as a result of a data architecture's elasticity.

1. Simple

Simple data platforms, simple frameworks for data assembly, simple analytic platforms, and a simple structure for easy data mobility are all necessary components of an effective data structure.

1. Safe

By identifying new dangers and delivering data only to those who need it, as determined by the company, today's data architecture provides security.

Various Data Architecture Roles and Their Salaries

Now that we have understood data architecture, its essential components, and its characteristics, we finally look into the salary that this domain can fetch you. After all, if your career choice doesn't have a great pay range, it will be difficult for you to make a mark. Below mentioned are a few popular data architecture roles and their respective annual salaries in India.

• Data Architect: INR 21,42,644 per annum
• Senior Data Architect: INR 25,60,483 per annum
• Data Modeler: INR 12,51,051 per annum
• Data Warehouse Architect: INR 12,51,051 per annum

Final Words

With that, we come to the concluding part of the article. We have successfully covered and understood data architecture, its essential components, characteristics, and the salaries of the roles under this domain. The career opportunities seem to be huge given the scope of it and the potential to earn.

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