5 Features of a Modern Data Architecture

5 Features of a Modern Data Architecture

Here are the key features of the modern data architecture that you need to look & understand the

Published By - Jason Hoffman

Data has become the new currency in the business world. Earlier data would only mean operational data and various databases. The proof of this lies in the fact that if you Google the term database or data architecture, you will receive responses such as Hadoop, NoSQL, etc. But when you have data coming in from all sides of the ecosystem, it becomes that much tougher to manage all of the data, and hence the importance of a modern data architecture creeps up.

What is Data Architecture?

Data architecture is a system in place in which all the data policies are defined in terms of collecting, organizing and using of the data. The previous data architecture was capable of handling the data of the past but the new data types require a more sophisticated architecture, and hence the need for modern data architecture components. Today, data is available from multiple sources such as sensor data, social media, IoT, operational logs, etc. and they are not similar in nature, thus requiring a new form of data architecture. Hence, following are some features of a modern data architecture and how they can benefit you.

Key Features of a Modern Data Architecture

1. Efficient Data Accessibility:
A major problem faced with handling data nowadays is its flow. The right data is not reaching the right people, and the modern data architecture takes care of this issue. It ensures that the data is accessible easily for the people for whom the data is relevant, and hence makes the data availability more effective.

2. Architecture Flexibility:
Most business data architectures are highly inflexible and are unable to handle the varied types of data available. With the modern data architecture framework, the high flexibility enables handling all types of data, as well as is compatible of handling and managing a newer type of data that might come up.

3. Scalability:
Scalability, either upwards or downwards is imperative to be considered in a modern data architecture. Many companies find it hard to implement scalability since they are skeptical about moving to the cloud, but a suggestion here would be to take a leap of faith and make the switch to the cloud and your data architecture will be scalable as per your requirements.

4. Resilience:
The thing with data is, as powerful data is, it is also vulnerable. This includes physical damage, natural disasters, outages, redundancies, failovers, etc. Hence it is imperative that the new data architecture is resilient in its processes to ensure even with all the issues, the data flow is unhindered. This is possible through some precautions such as mirrors, data backups, etc.

5. Ensure Strict Security:
Security has become a substantially large problem in the data world. With the major threat of data hacks and cyber threats looming everywhere, the need to beef up security measures in protecting data has grown more than ever. Every modern data architecture framework must be built from the bottom-up with security measures in place to ensure there are no leaks or loopholes existing in the system.

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