Published by Jessica Weisman-Pitts
Posted on April 20, 2022
5 min readLast updated: February 7, 2026
Add as preferred source on Google
By Scott Magill, Managing Director at Rubrik Australia and New Zealand
As the newest executives on the block, Chief Data Officers and Chief Digital Officers (CDOs) have some of the most critical and most complex roles in the C-Suite.
As every enterprise becomes a digital enterprise, their data only increases in value. As this evolution occurs, it’s paramount to have an executive dedicated to analysing and making sense of unstructured data to unlock the possibilities of personalisation and customer-centric services. However, there’s still much confusion over the CDO’s role and how they can bring greater value to the business.
Depending on the organisation, the exact scope of the position may vary but, by-and-large, every CDO will have three key responsibilities – data protection, data governance, and implementing or improving the enterprise’s data analysis function.
While all three are critical, one in particular has a more direct impact on moving the business forward – improving data analysis.
In other words, protection and governance happen behind the scenes while more effective data analysis empowers the organisation to make better business decisions and spend less calories to achieve higher rates of return.
Unfortunately, many CDOs get bogged down in the more legacy, resource-intensive methods of the protection and governance functions of their role. As a result, CDOs tend to have short tenures, high turnovers, and – in some cases – the role is eliminated only years after it was established.
For CDOs (both the Digital and Data variety) looking to make an impact on their business and earn a seat at the board table, it’s oddly helpful to think of these three competing responsibilities as players in the classic children’s game Duck, Duck, Goose.
Data Protection? Duck!
Without access to data, enterprises cease to operate, so it stands to reason that protecting this asset – commonly referred to as the ‘Crown Jewels’ – is one of the CDO’s primary tasks.
Unfortunately, cyber attackers know just how pivotal data is to business operations which has helped spawn the flourishing ransomware industry that leeches $1 billion from the Australian economy each year.
Ransomware is one of the biggest enterprise risks today. While the CISO has responsibility for preventing cyber attackers from penetrating the organisation, the CDO has to ensure business-critical data is recovered when the CISO’s defences are thwarted.
The CDO therefore has to ensure that when the inevitable happens, data and operations can be rapidly restored.
While this is an important function, it doesn’t move the business forward on its own. Its benefit – large though it may be – is only recognised in the wake of an attack.
Rather than get mired in the traditionally complex world of manual backups and data retention rules, thousands of backup jobs can be replaced with a few policies to automate data protection across the enterprise so the CDO can move on to bigger and better things.
Data Governance? Duck!
With the surge in data over recent years, along with the rise of the remote workforce, it can be difficult to keep track of where at-risk data is stored.
One of the CDO’s core roles is to wrangle the enterprise’s complex, sprawling infrastructure and ensure all sensitive data – such as customer and employee personally identifiable information (PII), payment data, or intellectual property – is appropriately stored.
Compounding the challenge of appropriate data governance are the myriad data privacy regimes enterprises operating internationally must adhere to – from the GDPR in Europe, to the alphabet soup of state-and-industry level regulations in the US, to Australia’s Privacy Act and Hosting Certification Framework.
Traditionally, just getting a bird’s eye view of where an organisation’s sensitive data is located has been an extremely time-consuming job that involved taking entire teams of skilled IT personnel away from more innovative projects.
As with data protection, data governance is an important remit of the CDO – as the reputational and regulatory risk of getting this wrong is immense – but it’s still one that doesn’t move the business forward. It minimises risk, but it doesn’t drive innovation.
CDOs should therefore look to leverage automation and machine learning to take over this function. With predefined policy templates, it’s possible to rapidly create an inventory of the enterprise’s data assets and document any sensitive data that is being stored non-compliantly.
Once this baseline is in place, CDOs can then be automatically alerted to any policy violations so sensitive data is always stored where and how it should be.
Extracting Data’s Value? Goose!
In 2017, The Economist declared data had overtaken oil as the most valuable resource.
Every year since, as data generation increases exponentially, this declaration has been proven true. But data in and of itself isn’t valuable. It is only when the insights within are analysed, extracted, and acted upon that data’s value becomes apparent.
This is where the CDO can have an outsized impact on their organisation.
Ensuring critical data is protected and governed in compliance with regulations is crucial, but the traditional approach to doing so is resource intensive.
Automating these functions enables the CDO to liberate highly skilled IT staff from the drudgery of backups and data inventory so they can turn their attention to actually using data, rather than merely holding it.
Imagine all the things a CDO could say ‘yes’ to if they had confidence in their data’s resiliency and governance.
Whether that’s creating new products, personalising services, improving internal efficiencies, or any other number of potential innovations, these are the initiatives that will keep the CDO at the board table.
A Chief Data Officer (CDO) is an executive responsible for managing and utilizing data as a strategic asset within an organization, focusing on data governance, protection, and analysis.
Data governance refers to the overall management of data availability, usability, integrity, and security in an organization, ensuring compliance with regulations and policies.
Data analysis is the process of inspecting, cleansing, transforming, and modeling data to discover useful information, inform conclusions, and support decision-making.
Ransomware is a type of malicious software that encrypts a user's files, demanding a ransom payment to restore access, posing significant risks to organizations.
Explore more articles in the Business category
