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Why Automated Policy Enforcement is the Backbone of Modern DataOps & Self-Service Analytics

Data is a key commodity that agencies can leverage for strategic advantage — if they can make it easy to consume and safe to share. As this data becomes more critical, federal agencies are actively engaged in data-driven activities, with some further along than others.

For agencies to realize the full potential of data-driven modernization, automating the enforcement of data access, privacy, and governance policies is crucial. Automated policy enforcement is the backbone of modern data operations (DataOps), which enables self-service analytics and expedites agencies’ digital transformations by removing data access bottlenecks.

Federal executives acknowledge the journey toward a true data-driven government will take time — just as the adoption and standardization of electricity took time to mature. That is why the Federal Data Strategy 2030 Vision lays out a 10-year plan for how agencies can build a robust integrated approach to managing and using data. Annual Action Plans follow an incremental maturity ladder that moves from foundational activities of governance, planning, and infrastructure to the data-driven activities of proactive evidence-based decisions and automated data improvements.

“Agencies that can make progress more quickly than outlined in the strategy are encouraged to continue promoting enhancement opportunities,” according to the 2021 Action Plan.

There are many challenges that can derail agencies from realizing their data-driven potential, such as more diverse cloud data ecosystems, the growing number of data consumers, and the rise of sensitive data use. Plus, regulations are becoming more common and more stringent, forcing agencies to rethink how they collect, store, use, and dispose of enterprise data. The good news is that as with electricity adoption, the growth in data availability has also given rise to systems designed to ease complexity.

Reduce Operational Overhead, Eliminate Bottlenecks

With data, it’s all about deriving new analytic-driven insights, whether you’re building artificial intelligence (AI)-based innovation into customer experiences or improving decision-making for national security missions.

Many organizations are turning to data catalog tools to manage their data. Data catalogs are useful, but they are primarily “lists” or inventories of data assets with built-in workflows to empower data stewards to manage them. While data catalogs do provide a front door to those assets, they don’t reduce the operational overhead associated with safely and efficiently enabling data consumers to access the data for analytics.

Given the volume, variety, and increasing velocity of data being created across agencies, a front door is not enough. With the ubiquity of the cloud, any agency that wants to accelerate transformation and become truly data-centric must employ tools that reduce operational overhead and eliminate bottlenecks, enabling users to consume data for analysis. At the same time, the tools must ensure data access policies are enforced and auditable, regardless of where the data resides. To that end, the entire data supply chain must be automated in order to make data inventories and data catalogs more operationally valuable.

Right Access at the Right Time

To more effectively use data to drive decisions via advanced analytics, agencies need an integrated, automation-driven architecture where data suppliers ensure the right access to the right data at the right time for users, while enforcing policies consistently.

The paradigm shift here is like the evolution of e-commerce. Early on, payment platforms were not fully integrated into the shopping platforms, and consumers waited days for a package to be delivered. Nowadays, e-commerce is preferred by most consumers, as it is a completely streamlined, automated, self-service process. Consumers can go online, click a few buttons, and in a brief period, sometimes less than two hours, have goods delivered to their door.

Automated data operations make it easier for users to operationalize the right data quickly and repeatedly, driving faster transformation across agencies. Additionally, capabilities such as sensitive data discovery and dynamic attribute-based access control (ABAC) streamline processes that would otherwise be time- and labor-intensive. By permitting or restricting data access based on assigned user, object, action, and environmental attributes, ABAC provides more proactive, flexible, and scalable access control than traditional, role-based access control models. In today’s world of increasing regulations, policies written in plain English can be audited on-demand, increasing transparency without slowing down approval workflows.

The Bottom Line

The lesson is this: If agencies really want a more data-centric government, they must make it easy for consumers to use data by removing bottlenecks in the data supply chain through automation. This means agencies must ensure their data policies are automatically enforced so they can open data up for analysis significantly faster, empowering data professionals via self-service data access. Data governance tools are available to achieve these goals as fast as possible.

Once these steps are solved, all existing data investments – data processing platforms; business intelligence tools; Extract, Transform, Load (ETL) and data movement tools; and AI development tools – will be able to deliver scalable, timely impacts to your agency’s mission.

To start automating data access controls and unlock your data’s full potential, request a demo of Immuta.

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