The importance of data modernisation for today’s organisations

by | Sep 7, 2023

The importance of data modernisation for today’s organisations

by | Sep 7, 2023 | Blog | 0 comments

The importance of data modernisation for today’s organisations

Nathi Dube, Director, PBT Innovation at PBT Group

South African businesses, just like their counterparts internationally, are grappling with the challenges and opportunities provided by the rapidly growing data ecosystem. A data modernisation and optimisation strategy has become imperative in this regard. Failing to modernise is fraught with risks that could imperil an organisation’s competitive stance, and its future viability.

With this in mind, I’ve outlined here what I believe to be the key aspects of a data modernisation and optimisation strategy:

  • Data estate analysis: The first step towards data modernisation is understanding your organisation’s current data estate. It’s vital to involve all stakeholders across departments to diagnose high-level data issues. Collaborative insights pave the way for a future-proof data architecture.
  • Unified data architecture: Modernisation involves assessing and redesigning the existing data architecture to leverage modern platforms. Integrating disparate data models and aiming for a consolidated data environment ensures improved efficiencies.
  • Embracing cloud: The discussion around data modernisation is incomplete without cloud integration. Modernisation increasingly implies migrating data to the cloud, using cloud-native capabilities, and leveraging cloud benefits like elasticity, scalability, and advanced tooling.
  • Business-centric data delivery: A modernised data architecture offers business-focused data delivery. Instead of being overly IT-centric, where business units wait for IT to extract or deliver data, a modernised approach provides immediate access, enhancing decision-making processes.
  • Continuous improvement with DataOps: DataOps is a collaborative data management approach that focuses on delivering insights swiftly through automation. It not only streamlines data delivery but also ensures consistent value extraction from data initiatives.

But one can’t justify the business case without examining the benefits of modernising and optimising data. As I see them, the potential business benefits can include:

  • Efficient data processing: Modernisation offers streamlined data processing by collating data from multiple sources, cleaning it, and making it readily available for analysis.
  • Enhanced data access: In a world where remote work is becoming the norm, data modernisation ensures data is easily accessible from anywhere while maintaining robust security measures. This not only supports remote work but also ensures sensitive data remains protected.
  • Boosting business growth: High-quality, standardised data underpins meaningful Key Performance Indicators (KPIs). These KPIs, when built on robust data, provide insights that guide strategic decisions, fuelling business growth.
  • Prompt decision making: With real-time data access and self-service analytics, organisations can make informed decisions swiftly, leveraging the most up-to-date data available.
  • Scalable data storage: Modern platforms can seamlessly handle structured and unstructured data, scaling according to the growing datasets and delivering insights in real-time.

Additionally, a considered approach would not be encompassing without also highlighting the perils of not modernising. In my view, avoiding the modernisation path can hamstring businesses in several ways, including:

  • Restricted data access: Legacy systems, being IT-centric, slow down the data access process, affecting decision-making efficiency.
  • Storage constraints: Legacy systems often grapple with limited storage capacities. Deleting historical data to create space not only results in potential data loss but can also make organisations non-compliant with regulatory mandates.
  • Integration hurdles: Legacy systems frequently struggle with integration, necessitating extensive custom coding. This not only incurs cost but also consumes time.
  • Deteriorated customer experience: Legacy systems, with their rigidity, inhibit organisations from providing modern, digital experiences that today’s customers demand.
  • Challenges in handling large datasets: Traditional systems lack the capability to manage large datasets effectively, preventing businesses from harnessing the full power of their data.

Given how rapidly the data landscape is evolving, the strategies to manage, optimise, and monetise data must also keep pace. Businesses need to look at data as being more than an asset. Rather, it is a catalyst for innovation, growth, and sustainability. Modernising and optimising data infrastructure is the path forward – and one that, if done strategically, promises to unlock unprecedented business value.


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