**London**: Organisations are redefining their IT infrastructures to adapt to rapid technological advancements. Data leaders, like Capital One’s Marty Andolino, stress the importance of creating centralised data hubs and governance policies to enhance data accessibility and support AI initiatives for competitive advantage.
Organisations across various sectors have increasingly embarked on digital transformations over the past decade, a shift that is now seen as an ongoing requirement to keep pace with rapid technological advancements. As organisations adapt, especially in light of recent developments in artificial intelligence (AI), there is an acute need to update foundational IT infrastructures and operating models.
Marty Andolino, Vice President of Engineering at Capital One’s Enterprise Data Technology, emphasises the necessity for data leaders to construct modern data ecosystems that ensure data remains governed and accessible for effective use. This is particularly crucial for those organisations aiming to leverage AI technology effectively.
In the context of digital transformation, an effective data management strategy involves establishing a scalable ecosystem that allows diverse teams within an organisation to locate, access, and utilise high-quality data. Andolino outlines several critical components to achieving this goal.
Central to a robust data management strategy is the creation of a centralized data hub. This unified repository consolidates data from across the enterprise, serving as the “heartbeat” of the organisation’s data ecosystem. By utilising a blend of proprietary and commercial tools, companies can develop a secure and efficient access point for real-time data sharing, which integrates distributed data sources into a standardised framework.
This central hub facilitates secure data provisioning to authorised users, supports the publication of data to lakes for machine learning initiatives, and permits real-time data streaming—all under a consistent set of governance rules and standards that ensure compliance across the enterprise.
Before initiating a large-scale data centralisation process, Andolino advises organisations to establish strong data governance policies. These frameworks are essential in defining data management standards, ensuring compliance with relevant regulations, and implementing measures such as tokenisation and data quality assurance. Such robust governance is crucial for maintaining data integrity and enabling secure data discovery across the organisation.
The next step involves constructing data pipelines to and from the central hub to facilitate federated data sharing. These pipelines organise data into manageable units that can be recombined for various applications, such as marketing teams merging transaction histories with demographic data to tailor campaigns and enhance customer experiences. This capability not only enhances the delivery of contextual insights but also promotes collaboration and decision-making across departments like sales and engineering.
A key factor in a successful data ecosystem is maintaining transparency and trust. As data traverses multiple systems, organisations must implement effective data lineage and monitoring tools to track its provenance and adherence to governance policies. This level of scrutiny ensures that data meets service level agreements and quality standards, enabling timely corrective actions when issues arise.
Andolino also notes the significance of addressing legacy data gathered over the years. Modernising this data—through processes such as cleansing and standardising—can render historically collected information accessible and functional within contemporary systems. This step is valuable for providing a comprehensive understanding of trends and past performances that influence future strategies.
In an environment characterised by rapid digital disruption, organisations recognise that data represents a competitive advantage, whether through the refinement of business strategies or enhancement of AI capabilities. Successful digital transformations hinge on leadership that advocates for a data-driven culture, fostering a strategic decision-making framework that not only addresses current needs but also prepares for future AI initiatives—essential elements in the evolving landscape of business technology.
Source: Noah Wire Services
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