In this guest blog post, Tim Ward, CEO and Co-Founder of CluedIn, addresses data governance and shares how modern tools can improve efficiency and enable revenue growth.
Businesses are constantly seeking ways to optimize operations and drive growth. One of the most powerful yet underutilized tools at their disposal is data governance. Modern data governance does a lot more than ensure compliance and security; it also plays a critical role in enhancing both the top and bottom lines of an organization. In this blog post, we will explore how leveraging advanced data governance strategies can lead to significant financial benefits.
At its core, data governance involves the management and oversight of data assets within an organization. This includes data quality, data security, data privacy, and compliance with regulatory standards. In the past, data governance was often seen as a purely defensive measure, focused on minimizing risks. However, modern data governance goes beyond risk mitigation, offering opportunities for value creation and competitive advantage.
Three ways to grow revenue via data governance
- Enhanced customer insights and personalization: Modern data governance tools, such as Microsoft Purview and CluedIn in the Azure Marketplace, enable businesses to discover, map, and clean customer data from various sources. By creating unified customer profiles, companies can gain deeper insights into customer behavior, preferences, and needs. This information allows for highly personalized marketing campaigns, tailored product recommendations, and improved customer service, all of which can lead to increased sales and customer loyalty.
- Faster time to market: Efficient data governance enables streamlined data management processes, reducing the time needed to prepare data for analysis. It also allows domain experts to manage data directly and proliferate that data to all of the teams that need it. With democratized access to high-quality data, businesses can accelerate product development cycles and respond more swiftly to market trends. This agility allows companies to capitalize on new opportunities faster, giving them a competitive edge in the marketplace.
- Innovation and new revenue streams: Data governance facilitates the discovery of new insights and patterns within data. By leveraging AI-driven data exploration, profiling, and validation, businesses can identify new business opportunities, innovate existing products, and create entirely new revenue streams.
Three ways to reduce costs via data governance
- Operational efficiency: Modern data governance solutions streamline data management, often through the use of AI and machine learning, minimizing errors and reducing the need for manual processes. This efficiency lowers operational costs, as less time and fewer resources are required to manage data. Automated data quality checks and compliance management also reduce the risk of costly regulatory fines and penalties.
- Reduced IT and infrastructure costs: By implementing cloud-based data governance solutions like Microsoft Purview and CluedIn, businesses can optimize their IT infrastructure costs. Cloud-native tools offer scalability, allowing companies to manage growing data volumes without significant capital investment in on-premises hardware. Additionally, cloud solutions provide built-in security and compliance features, reducing the need for separate tools and resources.
- Improved decision-making: High-quality, well-governed data is crucial for accurate and informed decision-making. By ensuring data accuracy and consistency, modern data governance enables business leaders to make better strategic decisions. This leads to more effective resource allocation, optimized supply chains, and improved overall business performance, all of which contribute to cost savings.
Bringing the business into the data supply chain
Each of the above benefits represents an opportunity for organizations to maximize revenue, improve profitability, and reduce costs. But their potency depends on one crucial factor: the ability to bring domain experts — who may not be technically fluent — into the data supply chain. The context and knowledge they bring is often the difference between a data governance program that is defensively competent and one that proactively and consistently delivers opportunities to create value.
This business-led, technology-supported approach (supported by a federated data governance model) should be the desired state of any data governance effort. This means that the tools used to facilitate it must also be intuitive enough for business users to adopt. Microsoft Purview and CluedIn are designed in exactly this way, for example through the introduction of low-code/no-code features, business concepts like data products, and copilots. The future of data governance is federated, and those who recognize that now will be best positioned to take commercial advantage of it.
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