Modern Enterprise Cloud Data Architecture

Data is an important asset that is needed by every business to compete successfully in today’s economy. However, the worth of data assets can only be realized if they are utilized strategically, consistently, accurately, and operationally over the business. Doing this has been challenging. To ensure great levels of SLA, accuracy, high availability, and data governance demanded by clients and business strategy, businesses nowadays are switching to data-as-a-service (DaaS) as a portion of their cloud data architect strategy.  

They must possess a modern data architecture position to leverage a DaaS approach completely.

What Is Data Architecture?  

Created by data architects, data architecture normalizes how businesses collect, keep, transform, distribute, and use data to help company data analysts make better decisions depending on real-time business intelligence. Data architecture is the foundation for information architecture and modeling, allowing data to be used and valuable throughout the organization.

As data architecture is nothing like a new idea, advanced enterprise data architecture (or advanced data architecture) has grown as enterprises increasingly transfer to the cloud. Only cloud architecture services provide scalability, ease of use, and speed required to make advanced data architecture effective. Companies’ data architecture is transforming as they move to cloud-related infrastructures. 

Who Is a Cloud Architect?   

A cloud data architect is an IT expert who supervises an organization’s cloud computing strategy. This involves cloud application design, monitoring and management, and adoption plans. Cloud data architects handle application architecture and deployment in cloud environments – involving the public, hybrid, and private clouds. They also work as consultants in their company and are required to stay updated on the latest problems and trends. 

Also, cloud architects might be involved in the legal parts of cloud computing, such as negotiating contracts and working with procurement and legal departments. Architects also make sure that service-level agreement needs are met.

What is Modern Data Architecture?

Modern data architecture emphasizes aligning data with capabilities powered by the cloud. Traditional data architecture was based on on-premise data models, which took significant time for data management and processing. With its infrastructure abstracted by the cloud, advanced data architecture emphasizes making data valuable and accessible to the company and clients. It enables ease, collaboration, speed, consistency, and real-time analysis.  

3 Phases of Modern Data Enterprise Journey

As companies are digitally changing and moving toward the cloud, they go through a phased journey to accomplish a modern data architecture. 

This can be divided into three main phases:

Phase 1 – On-Premises

Many companies own on-premises systems with the equipment to process and keep massive data sets and do complex transformations. This environment is challenging for the reasons mentioned below:

  • It takes a massive initial capital investment in advance to get going and a significant investment for operating expenses (OpEx) for the required staff.
  • It requires a dedicated and specialized skill set to handle the big data equipment.
  • It results in slow response times, including waiting times to purchase, shipment, and installation of data environments.

Companies have worked like this for decades and usually have significant investments for on-premise models. Not just the financial investment but also the risk of having data no more or disconnecting custom integrations can be much higher for full cloud migration. Many companies possess data that they feel should stay in the purview of the company’s servers and take a hybrid cloud approach for this reason.   

Phase 2 – Cloud: Virtual Private Cloud (VPC) 

Since they adopt the cloud, the following phase of the journey is “lift and shift,” in which companies move on-premises collections to a cloud architecture services provider that runs on a virtual private cloud network and can gain benefits out of laaS, such as reduced pricing. Forrester has reported that companies that deploy the cloud save between 20 to 60% on on-premises infrastructure costs. 

But this phase still has got some notable challenges as it:

  • Does nothing to confront the challenges of maintaining and managing the environment.
  • Has high OpEx
  • Does not confront the skill gap and required skills to handle the services which run in the VPC.
  • Has slow response time.
  • Doesn’t support any native cloud storage services.

Managing private and on-premise clouds is complicated, leading companies to find a better way to manage the cloud environment. It leads to a move to manage cloud services.

Phase 3 – Cloud: Big Data as a Service

At this phase, companies have identified the challenges and are confronting them by migrating to cloud-managed related services, such as IBM, Google, and Microsoft. These managed services release the company from the complexity of maintaining and managing the at-scale computing environments and reduce valuable OpEx spending.

Build a Strong Modern Data Architecture 

A strong modern business data architecture ensures businesses have the speed, flexibility, reliability, and accessibility of optimizing each data source and using it to make better business choices. Cloud architecture services providers provide data integration services with the help of its intelligent integration platform, which helps companies build advanced data architectures to meet their future needs.