5 Reasons for Government Agencies to Modernize their Data Warehouses With BigQuery

SADA Says | Cloud Computing Blog

By SADA Says | Cloud Computing Blog

As entire industries rapidly digitalize, citizens are increasingly demanding that public-sector agencies provide the same response, access, and ease of use they’ve come to expect from private-sector businesses. This is the crux behind federal IT modernization initiatives, such as the President’s Management Agenda, the OPEN Government Data Act, and the Cloud Smart Strategy, as well as state- and local-based digital government strategies.

IT modernization efforts require the right infrastructure. Many agencies, especially on state and local levels, are still operating on-prem legacy equipment and grappling with how to transition to a modern cloud-based IT environment. BigQuery, Google’s serverless, scalable data warehousing solution, provides a solid foundation for digital transformation. Agencies get the data analytics and machine learning capabilities they need to improve their decision-making while achieving superior data security, scalability, and high availability.

Here are the primary benefits of modernizing with BigQuery: 

1. Get Rid of Costly, Complex Licensing Fees

On-prem data warehouses are expensive, and licensing requirements are notoriously complex and confusing. In addition to paying costly hardware and software licensing fees, agencies are also saddled with the burden of ongoing systems engineering and maintenance. This is money and time that budget-strapped agencies cannot use to fulfill their missions or drive more efficient delivery of services.

When modernizing with BigQuery, agencies aren’t just migrating to the cloud; they’re migrating to an entirely new and lower pricing model. In addition to saving on the direct costs of licensing, agencies no longer have to engage in infrastructure maintenance or systems engineering.

2. Ease of Use for Both Admins and End Users

Traditional data warehouses are highly complex and require so much ongoing maintenance that organizations spend about 85% of their time on systems engineering tasks, such as resource provisioning, and only 15% on actually analyzing and deriving insights from their data. Additionally, end users find traditional systems quirky and very difficult to use. This is a major pain point for government agencies, which are already struggling to upskill employees in the face of a severe shortage of IT skills.

By automating systems engineering tasks and giving end users a far less complex user interface, BigQuery enables agencies to focus on analytics work that drives their missions instead of getting bogged down in systems administration. Agencies that migrate to BigQuery can reduce their total cost of ownership (TCO) up to 41% to 52%.

3. Deploy Smart Analytics at Scale

Traditional data warehouses were developed in the pre-cloud era and are not equipped to handle today’s data needs. Because these old systems don’t scale well, many data warehouses in use today are running at 95% to 100% capacity. At this usage level, queries end up running very slowly or stop altogether. Legacy solutions also don’t have the advanced analytics capabilities that can help agencies quickly distill the relevant insights they need to find solutions to complex problems.

BigQuery is self-scaling. It identifies the resource requirements that each query needs to finish quickly and efficiently, then automatically provisions those resources to meet demand, allowing it to execute queries in seconds, not minutes. Users can run lighting-fast queries on any scale of data, up to petabytes or down to kilobytes, all backed by the world-class availability and uptime of Google Cloud Platform.

4. Simplify & Enhance Data Security

Federal, state, and local government agencies are major targets for data breaches and other cyber threats. While traditional data warehouse solutions have security features, agency IT personnel must configure them on their own, and the settings are tricky to get right. Additionally, regular testing and reconfiguration are required to ensure protection against new and emerging threats in an incredibly dynamic cyber threat environment.

BigQuery removes the guesswork and legwork from data security with built-in encryption, automatic data protection, and data replication at scale. Administrators also get access to Google Cloud’s identity and access management (IAM) tools, which make it simple to control and automate access to encrypted datasets.

5. Access Advanced AI & Machine Learning Tools

With legacy data warehouses already running at capacity, and systems administrators struggling to maintain them, there are simply no resources to implement advanced predictive analytics tools that could help agencies solve complex problems and efficiently achieve their objectives.

BigQuery enables government agencies to access sophisticated artificial intelligence and machine learning features without having a team of data scientists on staff. The simple SQL interface allows non-technical end users to harness powerful machine learning models to perform predictive analytics. Because BigQuery is fully serverless and runs on the Google Cloud Platform infrastructure, it also integrates with a broad ecosystem of data and analytics partner tools.

By ditching clunky and archaic traditional data warehouse solutions in favor of the agile, serverless BigQuery, government agencies can lower their TCO, enhance data security, enable proactive decision-making, and fulfill their mission to serve the public.


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