5 Modern Data Architecture Fundamentals

Data Architecture is Rapidly Evolving

Data has become one of the most valuable assets available to modern businesses, providing them with valuable insights that can be used to make informed decisions, optimise operations and drive growth. However, the traditional approach to data architecture, which involves siloed (and often proprietary) data storage systems and complex ETL (Extract, Transform, Load) processes, has become increasingly outdated and inadequate for handling the volume, velocity and variety of data in today’s digital age.

This is where the concept of modern data architecture comes in. In essence, a modern data architecture provides a framework to leverage cutting-edge technologies and best practices to enable organisations to manage, process and analyse their data efficiently and effectively.

5 Key Components of a Modern Data Architecture:

1. Data Sources:

These are the systems, applications, and devices that generate data, such as databases, sensors, social media platforms, and mobile devices. The data from these sources is typically collected and ingested into the data warehouse.

2. Data Integrations:

This involves the process of combining data from various sources and transforming it into a format that can be analysed. Data integration methods, such as ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are commonly used to perform this task.

3. Modern Data Warehouse:

In contrast to traditional data warehouses, which focus on BI and feature rigid data models and moderate scalability, the Modern Data Warehouse (MDW) focuses on analytics, is highly scalable and enables flexible data models.

4: Datamarts

The flexible data model can be used to service multiple application datamarts. Each datamart can have its own data model and local data quality rules, pertaining to the application and the use cases of the end user.

5: Data Governance

This involves the establishment of policies and processes to ensure that the data is accurate, reliable, and secure. Such policies and processes include data quality rules, which often exist to remove duplicate data and validate data to check it’s accurate.

Flexible, Agile and Scalable

At its core, a modern data architecture is designed to be agile, flexible and scalable. It enables organisations to ingest and store data from a wide range of sources, including structured and unstructured data and external data sets. This allows organisations to gain a comprehensive view of their data and extract insights that would have been impossible to uncover with traditional data architecture.

Additionally, this flexible data model makes it easier to introduce new and/or unexpected data sources to be introduced in the future.

A modern data architecture also enables organisations to process and analyse data in real-time, making it possible to identify patterns and trends as they happen. This can be especially valuable for fast-paced industries, such as finance, transportation and e-commerce, where the slightest delay in data processing can result in missed opportunities or costly errors.

In addition, a modern data architecture incorporates best practices for data governance, privacy and security, as well as technologies for data backup, disaster recovery and high availability. This has the added benefits of both protecting organisations from data breaches (and resulting regulatory fines) and also ensuring that they are making the most of their data assets and investment.

In Summary

A modern data architecture is now a critical component of any organisation’s digital transformation journey. By enabling the easy management, processing and analysis of data, a modern data architecture also provides a competitive edge that can help organisations to innovate and thrive in today’s fast-paced business environment, while also future-proofing against new and emerging challenges.

Want to learn more about how your business can adopt the principles of a modern data architecture? Get in touch with our team today.

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