Enterprises Look for these 8 Modern Data Architecture Characteristics

Modern data architecture is the need of the hour due to the influx of big data

While many say data is the oil of an enterprise, I believe it is the heart of enterprises worldwide, irrespective of the size. Modern organizations are those that are rethinking their data strategy as per the current business landscape. Hence, these organizations are driven by modern data architecture, they can better predict their requirements and work towards enhancing them for better business results.

The reason organizations are moving from traditional data architecture to modern data architecture is because the former one lacks speed, agility, and volume, which are important aspects that organizations need today. Modern big data architecture fulfills these demands effectively, enabling enterprises to unify their data across various storage technologies.

Modern data architecture components should be reviewed that provide increased flexibility, agility and reduced time. Let's dive deep into the modern data warehouse architecture and look at the important characteristics of  modern data architecture.

Speed and Scalability

The modern BI architecture was designed to solve the challenges of traditional data architecture, especially, speed. The modern data architectures are hosted on the cloud, hence easily scalable. They are meant for taking care of huge volumes of data without affecting its efficiency even if the data is less. That way, enterprises can start small and modern architecture can support its growth.

Appropriate Interfaces

The modern BI architecture helps easy access to data. Having a single repository of data does not guarantee the seamless and hassle-free functioning of a data-driven enterprise. A shared data asset is necessary so that users can access data easily. A modern data architecture provides appropriate interfaces to consume data, which can vary depending upon the user's position and credibility in the enterprise.

Managing Different Forms of Data

One great advantage of a modern data architecture is that it helps to manage different types of data, be it structured or unstructured, cloud-based or on-premise-based. Also, it reduces the complexity of accessing data stored in different locations as it brings down to one place. Data silos, security, and governance are ordinary with the traditional data architecture. Since enterprise can, without much of a stretch, scale all over on the cloud, processing speed is not at all an issue. Hence, companies can easily harness insights from data.

Flexible

One of the key characteristics of a modern data architecture is flexibility. The pipelines are built utilizing base data objects, such as data snapshots,  master data, data views, etc. The data objects fill in as building blocks that are ceaselessly reused, repurposed, and renewed to guarantee the consistent flow of top quality, significant information to the business.

Self-serve

Modern data architectures are meant to encourage self-serve. Under self-serve, teams across the enterprise can work on a single copy of truth. Data is open to all divisions. This is not normal for the ETL world where departments are data isolated and they don't have the foggiest idea of what data is accessible to the other department.

Predictive Analytics

Technologies like artificial intelligence are also now a part of the modern big data architecture. Such data architectures can then provide predictive analytics, helping enterprises make better decisions. Artificial intelligence-empowered modern data architectures can help enterprises to spot patterns in data quickly.

Cost-Effective

Traditional data architectures lacked necessary components that are very important in today's cutting-edge world. Hence, it also became quite expensive to use them. As modern data architectures are hosted on the cloud, enterprises can pay as you scale. Thus, they contribute towards lower data management overhead as there is no need for data movement. Compared to an ETL architecture, the cost of ownership is also less in modern big data architectures.

Automated Capabilities

Automation eliminates the friction that made traditional data frameworks drawn-out to arrange. Processes that required a very long time to assemble would now be able to be finished in hours or days utilizing cloud-based modern data architectures. If a client needs access to various information, automation empowers the architect to rapidly plan a pipeline to provide it. As new data is sourced, data architects can rapidly incorporate it into the architecture.