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Effective Data Sharing at Scale: Insights from Bank of America’s Ramdas Narayanan

Ramdas Narayanan, Vice President of Product Management for Data Analytics and Insights at Bank of America, has over a decade of experience building effective data sharing at scale. This article explores some of Ramdas’s insights on implementing data mesh on the operational plane and leveraging data effectively using a data mesh framework. 

Data Mesh on the Operational Plane

Implementing data mesh on the operational plane isn’t easy. It requires organizations to build robust data infrastructure, develop and manage data products and services, and execute data-related processes and practices. Additionally, organizations must ensure data quality, enable data access and discovery, and foster a culture of data sharing and transparency. Challenges related to data discovery and the formation of data silos often arise during this process. 

Improving Data Discovery

Data discovery plays a pivotal role in extracting meaningful insights from data. Ramdas emphasizes the importance of educating business professionals on what data is available, as well as what data is not. “That clouded vision of what data is available creates a lot of frustration,” he explains. By providing clarity on what data is available, organizations can prevent stakeholder frustration and empower them to make informed decisions.

Ramdas suggests that organizations can enhance their data discovery capabilities by hosting information architecture meetings, which provide an opportunity for individuals to share data context and build a stronger understanding of available data. These meetings provide an opportunity for individuals to explore different ways to leverage data and can even spark meaningful conversations across teams. In addition to these meetings, data professionals can contribute to data discovery by enriching dataset metadata to include valuable information and better share context.

Ramdas emphasizes the need for continuous questioning and assessment of the data flow within the organization. By asking key questions such as “Why are you doing something?”; “What problem are we actually trying to solve?”; and “Do we have the capabilities to solve that challenge or that set of challenges?” organizations can promote effective data utilization. Stakeholders should also assess the overall data flow and processes within the organization by asking questions like “How does the data flow through our systems?”; “Can we push data quality upstream to proactively prevent quality issues?”; and “What guardrails can we put in place to prevent issues?”

By embracing a proactive approach to data discovery and fostering a culture of continuous assessment, organizations can maximize the value of their data resources.

Avoiding Data Silos

Data silos pose a common challenge for organizations implementing data mesh. Ramdas cautions against building solutions exclusively for specific problems, as this often leads to the creation of disconnected and fragmented datasets. To avoid data silos, organizations should instead prioritize creating cohesive and reusable datasets. By thoroughly studying data sources to identify valuable data that can be repurposed for other use cases, they can prioritize the data needed to create cohesive datasets.

Ramdas also suggests involving developers in understanding how business teams will consume and use the data to overcome the challenge of avoiding data silos. By understanding consumption needs, developers can recommend the most suitable approaches for data consumption, whether that’s APIs, web services, or custom batch deliveries.

By incorporating Ramdas’s insights into their data processes, organizations can enhance data discovery, avoid data silos, and build a scalable data mesh ecosystem.

Learn More about Data Mesh

This article covers key insights from Ramdas’s extensive experience implementing data mesh at Bank of America. To learn more about his approaches for building effective data sharing at scale, check out this episode of Data Mesh Radio. For even more information about how organizations are leveraging data mesh, check out this playlist of user journeys.

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