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A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the Construction Tech Review Advisory Board.

Head of Data Governance at Tyro Payments

Gemma Dias

Data Governance and Data Management

Gemma Dias

Gemma Dias

Data is one of the most valuable assets that an organization can own, demonstrated by the increasing number of data theft incidents around the world. In Australia alone, notifications of data breaches increased by 26 percent in the second half of 2022 (July – December) compared to the previous six months (January to June), according to the Office of the Australian Information Commissioner’s Notifiable Data Breaches Report, with the top sectors being health, finance (including superannuation) and insurance.


Like any valuable asset in business, in a corporate or commercial environment, it’s important to know where data is stored, how to care for it, who is using it, and for what purpose – and, of course, how to keep it safe and secure.


Benefits of Data Governance and Data Management


Data governance sets the policies, guidelines, and processes so that data can be used as a consistent, secure, and organized asset throughout its life cycle. Data management is the development and execution of these policies and processes to manage the information lifecycle and needs of the organization in an effective manner using the data governance framework.


Organizations that have successfully implemented a data governance framework will typically have incorporated the relevant data practices in their solutions.


These practices include:


• Defining business glossaries to have a common definition of terms;


• Classifying data to understand its criticality;


• Assigning ownership of critical data to ensure that there is accountability and responsibility for it;


• Ensuring that critical data, which includes personal, sensitive, and confidential data, is kept secure;


• Ensuring its quality is measured throughout its lifecycle, ensuring that it is fit for purpose;


• Data retention and data disposal practices to comply with data regulations.


Effective data governance benefits not just the business but also its customers and internal staff.


It helps the business to improve customer retention and revenue, reduce brand impacts through compliance, reduce costs and waste, and can also improve automation and speed to market.

When implemented successfully, businesses can offer their customers a better customer experience via more relevant product offerings and higher quality service, as well as trust that their personal data is safe.


Internally, there are also benefits for businesses. Staff are provided with a common data standard, transparent data definitions, faster and more accurate impact assessments, and reduced duplication of solutions and work. Once the data has been managed and organized, a data information portal can be used to find and translate available data to bring efficiencies into processes that would otherwise be cumbersome or error-prone.

AI and Data Governance


With the increased use of artificial intelligence (AI) and generative artificial intelligence (Gen AI), it has become increasingly important for organizations to have a well-defined data governance framework to keep data safe, retain customer trust, stay compliant with data regulations, and gain a competitive advantage in the market.

Most data governance tools now come with AI capabilities with automated detection and protection of personally identifiable information (PII), sensitive and confidential information. They can also generate glossary definitions of terms and data elements, which can be validated by data stewards.


Generative AI holds enormous potential for the future, as it can help solve complex problems and make processes more efficient


With machine learning (ML) algorithms, AI-based data governance solutions can detect cyber threats and notify business authorities in time. Modern AI and ML tools tend to reduce data cleansing time and monitor data effectively, which can enable businesses to focus on core company operations.


Generative AI holds enormous potential for the future, as it can help solve complex problems and make processes more efficient.


However, with great potential comes great responsibility too!


It is important to consider the ethical implications of using AI and Gen AI, as well as the data that we provide to it. We should be aware that we need to get consent before we provide any personal, sensitive, or confidential data to be used by any AI or Gen AI application. We also need to be aware of the serious consequences of AI technology that can generate fake data, images, or videos and how that could invade the privacy of individuals.


With cautious management of these risks, Gen AI has a lot of exciting potential for business, data management, health, creative arts, education, and medicine.


Businesses with a focus on effective data governance and data management practices will be better equipped and empowered to navigate these challenges and grow safely as they embrace new technologies.


Author Bio


Gemma Dias is a passionate data leader with more than 25 years of experience leading teams within a diverse range of industries, including telecommunications, retail and distribution, banking and finance, capital markets, hospitality, and financial services. Most recently focusing on the areas of Data Governance and Data Management, Gemma helps organizations not only become more effective and efficient in their use of data but also comply with regulations around the use of data so that the business is safe and secure.

The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.
The Leadership Perspectives forum brings together voices shaping construction technology and innovation. Participation is by invitation only. It features leaders who are not merely observing technological change, but actively contributing to it through digital transformation and execution-driven insights.
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