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From Data “Ownership” to Data “Collaboration”: Generating Business Value with Secure Data Sharing
From Data “Ownership” to Data “Collaboration”: Generating Business Value with Secure Data Sharing

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Imagine a world where data isn’t just a resource but a currency that drives innovation, efficiency, and growth. According to Gartner Research, companies globally can lose up to 30% of revenue annually due to inefficiencies resulting from incorrect or siloed data. In today’s fast-paced business environment, Data and Analytics (D&A) leaders are increasingly under pressure to align their data and AI strategies with business outcomes. This demonstrates increased RoI on D&A investments while driving resiliency, reliability, and trust.

Traditional approaches to leveraging and sharing data are reaching their limits. Siloed data, over-reliance on monolithic AI techniques, stakeholder resistance, inflexible data usage and governance, and perceived regulatory restraints often stall and derail collaborative enterprise AI initiatives. However, secure data sharing and collaboration with third parties, external agencies, and partners offer a path forward. By providing access to a broader range of information, data sharing enables better-informed decisions, accelerates research and development, and drives more personalized experiences. This article will explore an enterprise framework for leveraging data sharing and why it’s crucial in the AI era.

The Need for a New Approach

D&A leaders must reevaluate their strategies and plan for easy-to-use, trusted, and efficient enterprise AI involving:

  • Creating a Secure Data Foundation: Ensuring data is secured, governed, managed, compliant, accessible, and flexible for interoperability.
  • Leveraging Multiple AI Techniques: Using the right tool for the right job, with generative AI-driven data collaboration providing immense value.
  • Exploring Secure Data Sharing: Unlocking ecosystem benefits and driving a higher degree of contextual awareness with data.

Benefits of Data Sharing

According to Gartner’s Sixth Annual CDO Survey, data sharing is a key performance indicator for achieving stakeholder engagement and driving demonstrable business value. Organisations utilizing data sharing are 1.7x more likely to effectively show verifiable value to D&A stakeholders while creating high-performing D&A teams. Furthermore, Gartner’s Fifth Annual CDO Survey revealed that organisations sharing data externally with partners generate 3X more measurable economic benefit than those that do not. Organisations in India are leveraging data sharing and external datasets to improve processes, accuracy of AI and creating additional revenue streams by sharing their data. 

Framework for Enterprise Grade Data Sharing

Organisations can find immense value in data sharing. Here’s a framework to approach it:

  • Define Objective and Scope: Clearly outline the purpose of data sharing, the types of data to be shared, and the parties involved.
  • Security & Governance: Create a governance structure defining roles, responsibilities, and decision-making processes. Ensure the security of the data sharing mechanism and handle PII appropriately.
  • Communicate Value: Demonstrate the opportunity with data sharing vs. the lost opportunity without it. Highlight competitive advantages, product differentiation, and reduced time to value.
  • Tie Data Sharing & AI: Augment internal data with external data for better contextual awareness and model performance, addressing issues like concept drift and covariate shifts. The efficiency of your AI models are to a very large extent dependent on the quality of data used for training. Utilizing shared data allows for higher accuracy.
  • Democratize Data Sharing: Make the D&A journey transparent, democratized, and accessible. Utilize technology as an enabler for collaborative data sharing.
  • Change Management: Involve stakeholders to shift from a data “ownership” mindset to a “collaboration” mindset.
  • Leverage Marketplaces: Start with external data and application marketplaces, evolving to internal marketplaces for broader use.
  • Share Results: Evangelize data sharing within the organisation, industry, peers, suppliers, and vendors, sharing success stories.

Data sharing is an essential business capability that aligns organisations with their business goals. However, it must be done at scale to provide tangible business value. While following the framework to create a data sharing solution from scratch is challenging, D&A leaders must evaluate technology solutions that meet the above criteria and work with solution providers to demonstrate value. 

Data sharing can yield immense value and competitive differentiation when used in tandem with AI. When done right, data sharing enhances trust in D&A initiatives, significantly reduces risks, and improves outcomes. Embrace the shift from data ownership to data collaboration and unlock the full potential of your data.

Authored by Farhan Choudhary, Senior Product Marketing Manager and Evangelism, Snowflake

 


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