Top Characteristics of a Modern Data Architecture

by Dynamix Group Writer

Today, organizations across industries are witnessing growth by monetizing the massive pool of enterprise data lake. Decisions backed by data assists in taking proactive business decisions, anticipate customer needs with accuracy, and build core competencies. With enterprises tapping into advanced analytics to fine-tune operations, sales, and other business strategies, the journey often begins with transforming the existing data architecture. Since data holds the enormous possibilities for the business to grow, it gets tough for an organization to rely solely on traditional data architecture, which involves a lot of manual work and is unable to withstand huge volumes and varieties of data.

 

Let’s look at some of the characteristics of modern data architecture that lend them must-have values:

 

Result-Oriented:

Modern data architecture is focused on facilitating ease-of-use for the end-user. It handles the complex integration and representation of data in a way that brings out the hidden patterns and information while simplifying the use of technology for the end-users. It acclimatizes to the evolving demands of the customers, depending on the department and role of the end-users.

Scalable and Adaptive:

The speed of data to be ingested and analyzed in the future cannot be predicted and is perhaps a difficult task. What appears suitable today might not be sufficient to cope with the required storage and processing capabilities. Real-time streams and micro-batches of data can be handled using modern data architecture. This is possible through the creation of a series of interconnected pipelines right from the ingestion of the data set to deliver the required information to the end-user by the modern data architecture.

Decoupled Architecture:

Modern data architecture drives innovation like no other as it is based on decoupled architecture where there’s no reliance on one service on another, making it completely distinct from the conventional architectures. Due to high portability and interoperability, it is capable of replacing a portion of the data pipeline with any other tool. Modern data architecture is compatible with leading open-standard tools and platforms.

Processing Real-Time Data Streams:

Modern data architecture is capable of ingesting and processing real-time data. It facilitates smarter business decisions with the help of statistical models and machine learning. Whether you need to display the right advertisement to a prospect based on his past behavior or send an instant alert to a user in the event of fraud recognition, modern data architecture is capable of doing it all. It also allows real-time governance to integrate and optimize data, thereby eliminating data swamps.

 

 

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Created on Jun 9th 2020 01:46. Viewed 343 times.

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