Building an agile government with cloud-based analytics

From patent approvals to econometrics, government agencies rely on efficient data processing and analysis to carry out their duties. By some estimates, the use of digital records in the Obama administration will create more data than all previous administrations combined.

Unsurprisingly, the explosion of data volume, variety and velocity in the federal government has created enormous challenges for acquiring technology and talent to meet the surging data analytics need. As a result of that "analytics gap," many federal agencies are struggling to meet their mandated objectives.

Civilian institutions have successfully devised a solution through the powerful combination of public cloud and open-source analytics software. The proliferation of public cloud offerings has eliminated the high fixed cost and long lead time historically required to procure complex analytics infrastructure. In addition, the public cloud is especially well suited for seasonal or unpredictable workloads -- it can dynamically scale the analytics infrastructure up to meet high demand and shut down unnecessary capacity as needed to reduce costs.

At the same time, the maturity of powerful open-source technologies, such as Apache Spark, in the cloud has provided cutting-edge capabilities previously only available in esoteric and cost-prohibitive proprietary software. In the case of Spark, superior performance, flexibility and ease of use helped the technology rapidly gain widespread support in the developer community and propelled it to become the de facto data processing standard. Today, a plethora of multinational enterprises ranging from Toyota to Bloomberg use open-source software such as Spark to solve many sophisticated problems, including monitoring sensor data and detecting fraud.

Given the establishment of public clouds dedicated to the federal government, agencies can also take advantage of the technology. Likewise, open-source analytics software is readily available via Amazon Web Services' government cloud offering. In short, the stage is set for agencies to embrace the latest cloud-based data analytics technology -- just like their civilian counterparts -- and tackle more sophisticated problems while staying within budget constraints.

For those who are planning to migrate to cloud-based analytics, there are three simple best practices to keep in mind to maximize its potential:

Embrace technologies endorsed by the developer community. The best open-source projects evolve at a frenetic pace because of contributions from the developer community. Choosing software with broad support enables you to capture the benefits of rapid innovation while advertising your organization as an attractive place to improve one's skills with elite peers.

Think holistically about your needs. For most organizations, the true power of analytics stems from combining different approaches -- such as real-time stream processing and machine learning -- to answer more complex questions. Understanding the different scenarios your organization might encounter in the next three to five years and choosing the technology foundation that can tackle them will allow you to future-proof your investment.

Offload noncritical work to maximize productivity. When working with sophisticated technologies, a significant amount of maintenance (e.g., upgrading and patching software) is necessary to keep the infrastructure operational. However, those tasks reduce the productivity of the teams responsible for delivering analytics. Unlike on-premises approaches, the cloud provides an easy solution to mitigate the burden in the form of managed services that allow routine maintenance tasks to be offloaded via automation software, enabling your team to focus on the mission.

With these best practices in mind, the powerful combination of cloud and open-source software will allow agencies to eliminate lengthy wait times to procure infrastructure, attract and retain top technical talent, and meet the growing demand for analytics. The government faces greater challenges today than ever, but armed with the latest and greatest in analytics technology, agencies will be empowered to carry out their missions more effectively.