Services Catalogue

Adopt cloud-based data management and cloud-based data storage.

Add a data fabric architecture for seamless integration. Organisations are looking for flexible data management solutions as data continues to sprawl across disparate destinations—on-premises data centres, multiple clouds, and edge devices.

You are Awesome. Don't forget it.

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Data Advisory

Novon guides organisations in formulating and refining their data strategies, aligning data initiatives with business objectives, and identifying opportunities for innovation.

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Data Architecture

Design and optimise the blueprint for storing, organising, and accessing enterprise data, ensuring scalability, performance, and alignment with current and future needs.

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Data Governance

Working with our clients, we help establish the frameworks, policies, and processes to manage data as a strategic asset-ensuring quality, security, and compliance that meets the organisation’s needs.

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Data Science & Analytics

Transform raw data into actionable insights through statistical analysis, predictive modelling, and AI solutions, driving data-driven decisions and innovation.

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Data Migration

With Novon’s deep experience, we ensure efficient and risk-mitigated transfers of data across systems or platforms, preserving data integrity and minimising business disruption.

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Data Integration

Connects diverse data sources and systems to create a unified view of data, enabling seamless data flow for better insights and operational efficiency.

What’s driving a modern Data Architecture?

In today's digital economy, data is a critical asset that drives business innovation, efficiency, and a competitive advantage. A modern data architecture is at the heart of leveraging this business asset. It is designed to address the complexities and scale of managing data in a rapidly evolving technological landscape. So, what are the key tenants of a modern data architecture that allow for this agility, innovation, and security of your organisations data.

Adopt cloud-based data management and cloud-based data storage.
Add a data fabric architecture for seamless integration. Organisations are looking for flexible data management solutions as data continues to sprawl across disparate destinations—on-premises data centres, multiple clouds, and edge devices.
Add a data mesh architecture to simplify and focus your response to the changing data landscape. It will enable your organisation to respond quickly and cost effectively to the data changes that abound in 2024
Adopt automation using generative AI and ML in data management.
Adopt low-code / no-code for data integration. Find the vendors or data specialists that have completed work similar to your challenge. Successful experienced operators are key.
Provide data governance, security, and privacy in an automated fashion. There is no time in 2024 to manually rediscover and develop data changes that other organisations have already found and adopted. These changes must be automated through generative AI and ML capabilities.

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Data management guiding principles still apply in today’s data landscape, however, today change is very rapid and there is no room for a bottom-up approach to managing your data, rather you should build pervasive AI / generative AI / ML models that do the heavy lifting for you.

In 2023 and still today we talk about data gravity as a key challenging principle of today’s modern enterprise data platform, but increasingly anti-data gravity is seen as the key issue in 2024 and beyond.

Data gravity is well documented, essentially this is where the accumulation of data (operations and analytical) attracts more data and services into its business data mix, thereby increasing data complexity and potentially causing serious challenges for an organisation to maximise the value of their data, especially if you have adopted a cloud first approach for your infrastructure. To further complicate this scenario, consider the challenges if you are a global organisation as you manage across different time zones, regulatory and business structures.

Anti-gravity advocates that the data and expertise should stay local and the two modern data architectures when used correctly can help moderate these challenges are data fabric and data mesh architectures.