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Why a meaningful data strategy requires more than an action plan

The Trump administration recently released a Federal Data Strategy draft action plan, outlining a series of ambitious — and at times ambiguous — steps for responsible governance of federal data use. The action plan is a significant and positive step for the government, where leaders seem to be arriving at a critical consensus: Agencies have a lot of data, and they need guidelines for protecting it and making the most of it.

Many of the action items in the draft Federal Data Strategy hold substantial promise, including establishing a data ethics framework; creating a repository of tools and resources for agencies; designating pilot programs for testing out new applications; and developing measures for workforce training and cross-agency collaboration. If and when these action items are realized, they will put government agencies miles ahead in their ability to maximize data, improve security and better serve constituents.

But the Federal Data Strategy — perhaps purposefully — doesn’t address some of the realities of today’s data usage and requirements. Already so many of the government’s missions and applications are heavily data-driven, but built on a patchwork of infrastructure, providers, strategies and architectures. Too often, data becomes collateral that’s dragged into other decisions: IT modernization, cloud migration, solutions providers and more.

Savvy leaders understand the power of data, but what they may be missing is a unique, separate plan that ensures their permanent ownership, security and control over that data. A standalone data strategy, developed independent of providers, cements an agency’s control of its own data indefinitely and provides flexibility, portability and consistency. Most importantly, this independent data strategy provides choices: in vendors, in collaboration and in all the different uses and types of data possible now and in the future.

Without a data strategy, your agency is vulnerable

If your data strategy is just part of your cloud strategy, then you don’t really have a data strategy — you’re at the mercy of your solution provider’s policies and decisions. Without a separate data strategy, there are no options for choosing the technologies and making the choices that best benefit your specific agency and its needs.

The lack of distinct strategy, and the preferences it affords, also risks vendor lock-in. Agencies continue to move away from proprietary systems and stovepiped technologies as leaders increasingly understand IT’s impact on their unique challenges and approaches. We’ve seen time and again the ramifications of single vendor lock-in: missed opportunities, siloed operations and greater expenses when even routine upgrades are exaggerated in cost and complexity.

In today’s growing IT market there’s a proliferation in options for hardware, software and containerization, giving agencies the option to choose where their data resides. Failing to recognize that data should have the same freedom and portability is an unnecessarily complex step backward.

Creating a standard also creates new opportunities

It’s well-known that culture and skill sets are additional major challenges for agencies as they lean forward into digitalization. Having an established, autonomous data strategy helps with workforce hurdles, as well: A uniform approach reduces complexity, increases security and offers standardization that better equips a workforce that’s no longer spread a mile wide and an inch deep on a variety of architectures.

Standardization greases the wheels for better collaboration, too. There’s tremendous value in sharing data and combining information and forces for the greater good. Furthermore, having a strong governing strategy allows agencies to take advantage of tools like open data platforms, which help foster cooperation and innovation. Capitalizing on these benefits hinges on data that can communicate — having an overarching data strategy and architecture that spans formats and environments facilitates sharing.

The government’s data is almost inevitably highly sensitive and mission-critical, and it needs to be held in high regard. This means that for the government the bar is incredibly high, and success is measured in a different currency: There really is no acceptable downtime and the impact level is very high if effective data security and governance is missing. As the speeds and feeds of data continue to rapidly expand, legacy infrastructure and approaches are not suitable for tomorrow’s unknown.

The good news is that agencies don’t have to start from scratch to create their data strategy. By leveraging examples and references from across government and industry — and by taking cues from guidance like the Federal Data Strategy — leaders can integrate best practices and options that fit their particular agency needs and the technologies they’re using now — and whatever they may use in the future.

Shaun Bierweiler is vice president and general manager of public sector for Cloudera, which provides enterprise data, cloud and analytics services.

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