To help federal agencies maximize innovation efforts, Collibra and Accenture Federal Services recently hosted ‘Enabling a Federal Data Mesh,’ a webinar to demonstrate the data mesh experience and illustrate how it can accelerate data discovery and speed time-to-value for federal agencies.
It’s a digital world
The truth is that in an increasingly digital world, the need for organizations to be data-driven has never been more pronounced.
The federal government is no exception.
But what does it mean for federal agencies to be more data-driven, and why is this shift important?
Today’s citizens, accustomed to the speed and personalization of digital experiences, expect no less from their government.
For the federal government to modernize and meet the needs of the contemporary citizen, it must tap into the vast reservoirs of data at its disposal.
This is not just about speed and efficiency. It’s about making informed decisions that impact the lives of millions.
From initiatives like the Evidence Act to the White House’s Blueprint for an AI Bill of Rights, there is an intense focus on leveraging data to drive innovation in government.
The question now is how can federal agencies drive data intelligence that not only keeps pace with the times but also spurs innovation? And how can data be used to make processes faster, more efficient, and more in line with the needs of today?
The answer: Data Mesh
If you’re a data professional, you’ve probably heard of data mesh (we wrote a series of blogs about it recently.) Its application, especially the principle of treating data as a product, offers significant benefits for leaders who need to move to a more data-driven model.
At its core, a data mesh is a decentralized data architecture and organizational structure. It pivots away from traditional monolithic and centralized data platforms, opting instead for a more distributed model where teams own and deliver data as products.
As a social and technical approach, data mesh can pave the way for more robust, scalable, and dynamic data ecosystems.
Federal agencies, federated by nature, with multiple components often working on independent but interconnected missions, can leverage the decentralized approach of data mesh to increase access to trusted quality data across the enterprise. Within Agencies and Departments, individual components maintain deep technical and business understanding of the data that they produce. Data mesh helps foster innovation at the component level by not requiring a one-size fits all approach at the enterprise level by providing a framework to make data highly discoverable through reusable data products.
Data-as-a-product explained
The data-as-a-product mindset involves treating data not just as a byproduct or a passive asset, but as a valuable product in and of itself.
When we treat data as a product, we apply product thinking to data, including:
- Researching the users of this data
- Developing insights about user needs
- Iterating on product feedback from users
Above all, the ‘data-as-a-product’ principle ensures that data is always measured by the value it brings to the people who use it.
Since the data mesh organization includes domain-driven ownership, the people who know the most about the data are in the best position as stewards of their data products.
Data mesh best practices
Embracing a data mesh isn’t without its challenges.
Since data mesh is as much an effort at rearchitecting social and cultural practices as it is a technical approach, successful agencies will achieve more value from a data mesh initiative that is backed by effective education.
Here are some best practices:
- Get people invested: The transition to a data mesh model requires cultural change. Encourage teams to see the value in data and foster a sense of ownership.
- Deliver access: Ensure that while data is decentralized, it remains accessible. Implement robust data governance and clear access protocols.
- Expand role of data owners: Data owners should not just be custodians but also advocates for the data they oversee. They must ensure data quality, relevance, and timely updates.
Get support from the Federal Data Mesh Accelerator
Accenture Federal Services’ Data Mesh Accelerator helps federal agencies jumpstart their data mesh journey by providing an industry-tested experience that allows users to discover trusted, quality data.
The Accelerator, built in Collibra, contains a custom self-service portal with the workflows and templates required for setting up, managing, growing, and governing a data mesh.
Users experience data mesh from the perspective of data consumers, data producers, and data governance members – providing a human-centric approach to define and establish the data product framework.
- Interactive: Data mesh self-service portal allows users to interact with the mesh and experience the transformative power of data-as-a-product.
- Streamlined: Templated and automated workflows provide a seamless experience for data consumers, data producers, and governance members.
- Secure: Data governance and fine-grain data access control support a secure zero trust complaint data mesh.
The Federal Data Mesh Accelerator comes out of the Accenture Federal Services Discovery Lab, which integrates design, discovery, and data to explore emerging technologies and prototype new capabilities. Visit Accenture.com/FederalAppliedIntelligence to learn more.
Be sure to watch the webinar ‘Enabling a Federal Data Mesh: How Federal Agencies Can Maximize the Benefits of Data Mesh,’ from Collibra and Accenture Federal Services.
Marjorie Willner, Ph.D. is a Data Science Manager at Accenture Federal Services and the Machine Learning Technical Area Lead within Accenture Federal Services’ Applied Intelligence Center of Excellence, the Discovery Lab. Marjorie has supported multiple federal agencies in the delivery of self-service analytics and is currently focused on helping agencies realize the potential of Data Mesh to meet their business needs.
Jay is an experienced leader who helps people get value from data through exercising his passion for enablement. As Head of the Data Office for Collibra, Jay provides modern, self-service data infrastructure, so that Data Analysts and Scientists across the business are empowered to create and manage their own value-driven Data Products. Jay enjoys the opportunity to be the internal customer of Collibra’s own products, ingraining “Collibra For Collibra” into the culture, showing the art of the possible. As a curious, lifelong learner, Jay loves teaching, mentoring, coaching, and elevating his teammates and colleagues to constantly challenge the status quo.
Simla Sivanandan leads the Data Intelligence team at Collibra. She firmly believes that Data Intelligence is about understanding the effect data can have on decisions, and offering the ability to create that impact. She is also a strong advocate of simplified and automated policies and processes that reduce friction and increase collaboration. Her team uses the Collibra Data Intelligence Cloud to drive these objectives and provides the community at Collibra with the ability to contextualize and trust the data, empowering our data citizens to use that data correctly and cohesively.
