Data driven digital transformation

Issue 8 2021 IT infrastructure

At the core of any data strategy lies the need to fully manage and exploit data as a strategic asset throughout its life cycle across the enterprise. This has proven easy for companies born in the cloud, but inherently challenging for organisations that are not.

Becoming data driven requires the will, capacity, resources and discipline to rethink how a business operates from people to processes as well as the technology that glues these elements together.

So great and widespread is this challenge that a group of highly respected data experts created a manifesto ( that makes the following appeal: “Your organisation’s best opportunities for organic growth lie in data. Data offers enormous potential to create competitive advantage, new wealth and jobs, improve health care, keep us all safer and otherwise improve the human condition.” Many companies are succeeding with small scale analytics, governance, quality and other efforts, still we find no examples of fundamental, lasting, company-wide change without committed leadership and the involvement of everyone at all levels of the organisation and we are fully aware how difficult it will be to unlock.”

The future of data management

While businesses wrestle with the challenge to become data driven, data management technology providers have been hard at work making the data dots easier to join. The most significant advance has come with the application of emergent advanced analytic, machine learning and AI techniques on the data itself, unlocking the highly optimised possibilities of augmented data management.

According to a 2021 Gartner Analytics trends report, “Augmented data management: metadata is ‘the new black’. Organisations utilising active metadata, machine learning and data fabrics to dynamically connect, optimise and automate data management processes will reduce time to data delivery by 30% by the year 2023.”

Data fabrics set the standard for a future of data management that promises to connect all data assets through an intelligent automated virtualised layer. While this is exciting, it is still early days and requires the integration and maturing of many varied data management disciplines and technologies to fully realise and prove its potential.

In the meantime, market leaders in data have re-written their solution offerings to incorporate these modern capabilities by creating cloud native, metadata driven and intelligent data management platforms.

These platforms are rich in capability and are the precursor to what data fabrics promise to be and I, for one, cannot wait to see these advances take hold and turn the South African economy into a data marketplace.

Welcome to the data marketplace

In our now modern digitally connected world, data is on the move at speed and at scale. Organisations need to seize this opportunity or lose competitive advantage. For this to happen, data needs to be organised in such a way that it is both intuitive and safe for the digital value chain (humans, applications and machines) to access.

Intelligent data management platforms are striving to achieve this by developing the building blocks to deliver on a unified ‘data marketplace’ which elegantly and efficiently facilitates the exchange of exponentially rising amounts of data (supply) to ever increasing interested parties seeking to extract value from it (demand).

These platforms have also been designed to be cloud native – able to deal with the flexibility and elasticity required to handle the sheer volume in supply and demand. Organisations are looking to cloud to modernise their applications to extend their reach and digitally engage their customers and stakeholders.

Imagine a single place where any user can access trusted and verified data, regardless of type or latency.

While the cloud creates the scale, this layer of governance creates the trust. Trust, scale and automated intelligence are the most critical enablers to powering true digital transformation. Our current methods and technologies simply do not have the design and capabilities to meet this challenge.

At its most basic level, this data marketplace allows a user to look for or discover data (using technical and business metadata), verify its quality and freshness, trace its origin (lineage), confirm or assign ownership (governance), apply a policy (e.g., PoPIA) or encrypt before safely ‘checking out’ the data for its intended use.

This sounds simple but involves the coming together of many data management disciplines and capabilities from across multiple data sources and users (including machines and applications).

Analysing the business impact

Businesses have made significant progress in unifying their fragmented data initiatives within the confines of their organisations. The above-mentioned marketplace builds on these efforts by simplifying the access (including integration) and sharing of this data in a uniform, standardised and scalable manner.

For example, a data marketplace can provide automated data driven responses to digital engagement platforms to ensure the promise of a hyper personalised customer experience is actually realised.

To achieve this, data is ‘served up’ and orchestrated between a variety of sources and role players (business users, data scientists, regulators), while taking care of deep data disciplines like finding/sharing customer records, enriching these to a full 360-degree view, identifying and masking sensitive information, facilitating mass internal (transactions) and external (interactions) integrations and transformations, AI driven automation of data related tasks etc.

This ‘data democracy’ ultimately accelerates cloud-based digital transformation, driven by trusted data.

The impact on business is only limited by our ambition and can stretch way beyond customer experience into supply chain, operational and other business innovations and efficiencies. Time to value for data scientists also dramatically improves by facilitating simplified accelerated access to trusted data, so that more time can be spent on insights and predictive models and less time is wasted on wrangling data.

The reality is that this technology capability is imminent, yet businesses themselves have to put priority and focus into maturing their data culture in order to actually absorb it.

As implored upon us by data leaders, this requires committed leadership and enterprise-wide change around the alignment, attitude and disciplines for treating and managing data as a valuable asset that enables and drives digital transformation.

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