Harnessing Real-Time, Integrated Data to Accelerate ESG Initiatives
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Environmental, social, and corporate governance (ESG) issues are increasingly important as organizations strive to build their brand reputations and earn customer trust. ESG encompasses a wide range of principles, from sustainable financing to ethical practices, which go beyond traditional financial performance. IDC estimates that global spending on ESG business services will soar to an astounding $65.0 billion by 2027, reflecting the growing significance of ESG in shaping the future of organizations.

Navigating ESG Challenges That Impede Value Creation

While the value of ESG is widely recognized, translating ESG aspirations into tangible action presents numerous challenges. One of the key hurdles lies in effectively managing the complexity of leveraging vast amounts of ESG data. This complexity arises from the need to identify and access data from diverse data sources, such as cloud platforms (often multiple), on-premises systems, decommissioned systems, and even supplier systems, to gain a comprehensive view across the entire supply chain. The mere task of identifying these sources can be overwhelming, let alone the tasks of integrating, securing, governing, and utilizing the data for analysis and reporting.

Adding to this complexity, integrating the data through traditional, batch-oriented methods can result in outdated or stale data, which would further hamper an organization’s ability to make timely, informed decisions, hindering progress towards their sustainability goals. Legacy IT systems, often locked into proprietary architectures and burdened with intertwined point-to-point integrations, struggle to keep pace with the rapid digitization sweeping across industries. This leaves leaders facing the dual challenge of advancing their ESG goals while also keeping operations stable and reliable. To overcome these obstacles, organizations need innovative solutions that not only support ESG objectives but also enable organizations to keep up with evolving digital and regulatory demands.

Unlocking Success with Data Fabric

One such solution is data fabric, which has emerged as a modern, successful data management strategy that streamlines the integration, management, and utilization of enterprise-wide data, in real time. As Gartner mentioned in a report from June 2021, “ Data fabric offers significant automation functions in the data management space. These include automation of data recommendations, data quality, data governance and policy, on top of the core integration functions of data virtualization.”

Data fabric eliminates the need to copy or move data, enabling organizations to move quickly and build analytical reporting with fresh data, as well as to operationalize the use of data through APIs. According to Gartner research, “Data fabric reduces time for integration design by 30%, deployment by 30%, and maintenance by 70%.” Using a logical approach with data fabric enables organizations to build a unified semantic layer that seamlessly integrates data from multiple sources, regardless of its physical location. Whether the data is stored across diverse cloud platforms, disparate on-premises systems, or different countries with strict data regulations, data fabric provides the agility and flexibility required to navigate complex data landscapes, as organizations do not need to physically move the data.

Through data catalogs, data fabrics empower users at all levels within the organization to leverage real-time insights for informed decision-making. As data fabric enables the embedding of data governance and access controls within its framework, organizations can leverage it to maintain data integrity, security, and compliance throughout the data utilization process. With robust data preparation capabilities, data fabric can further simplify data consumption, normalizing formats in which business and analytics users are able to discover and use the data. This gives them the speed and agility to deliver solutions to the business.

Data fabric goes beyond streamlining enterprise and ESG data management. It empowers businesses to automate processes, embedding analytics into day-to-day business operations, and harnessing the power of machine learning (ML) and predictive analytics. By infusing analytics into business workflows, organizations can unlock new efficiencies, identify patterns and trends, and make data-driven decisions that propel their ESG initiatives forward.

One remarkable story attributed to the implementation of data fabric using a logical approach concerns Festo, a manufacturing automation business with 300,000 customers worldwide. Festo used a data fabric enabled by the Denodo Platform to maximize energy efficiency and provide instant visibility on energy usage directly to shop floor teams. Festo also realized that with this approach, the company’s business users now had more flexibility to drive and maintain their own dashboards, which freed up IT for other tasks.

Enabling Seamless ESG Initiatives

In the dynamic landscape of ESG initiatives, in which organizations need to navigate the complex territory of sustainability and responsible business practices, data fabric emerges as a transformative solution. It has the capability not only to address the challenges of ESG data management, but also to enable organizations to leverage data as a strategic asset for driving positive change. By seamlessly integrating data in real time from diverse sources, enabling automation and embedding analytics into business operations, data fabric unlocks new possibilities for informed decision-making, efficiency gains, and sustainable growth.

Aditya Malik