The recent AI Executive Order aptly states that AI reflects the data upon which it is built. Federal agencies are looking to responsibly implement cutting-edge IT innovations such as artificial intelligence, machine learning and robotic process automation to improve customer experiences, bolster cybersecurity and advance mission outcomes. Accessing real-time, actionable data is vital to achieving these essential objectives.
Comprehensive data management is key to unlocking seamless, personalized and secure CX for government agencies. Real-time data empowers informed, rapid decision-making, which can improve critical, high-impact federal services where time is of the essence, such as in response to a natural disaster. Alarmingly, only 13% of federal agency leaders report having access to real-time data, and 73% feel they must do more to leverage the full value of data across their agency.
While some agencies are making progress in their IT modernization journeys, they continue to struggle when it comes to quickly accessing the right data due to numerous factors, from ineffective IT infrastructure to internal cultural barriers.
Actionable intelligence is paramount. The ultimate goal is to access the right data at the right moment to generate insights at “the speed of relevance,” as leaders at the Defense Department would say. To achieve the speed of relevance required to make real-time, data-driven decisions, agencies can take steps to enable quicker access to data, improve their data hygiene, and secure their data.
How to effectively intake and store troves of data
From a data infrastructure perspective, the best path to modernized, real-time deployment is using hyper automation and DevSecOps on cloud infrastructures. Many federal agencies have begun this transition from on-premises to cloud environments, but there’s still a long way to go until this transition is complete government-wide.
Implementing a hybrid, multi-cloud environment offers agencies a secure and cost-effective operating model to propel their data initiatives forward. By embracing standardization and employing cloud-agnostic tools for automation, visibility can be enhanced across systems and environments, while simultaneously adhering to service-level agreements and ensuring the reliability of data platforms. Once a robust infrastructure is in place to store and analyze data, agencies can turn their attention to data ingestion tools.
Despite many agency IT leaders utilizing data ingestion tools such as data lakes and warehouses, silos persist. Agencies can address this interoperability challenge by prioritizing flexible, scalable and holistic data ingestion tools such as data mesh. Data mesh tools, which foster a decentralized data management architecture to improve accessibility, can enable agency decision-makers to capitalize on the full spectrum of available data, while still accommodating unique agency requirements.
To ensure data is accessible to decision-makers, it’s important that the data ingestion mechanism has as many connectors as possible to all sources of data that an agency identifies. Data streaming and data pipelines can also enable real-time insights and facilitate faster decision-making by mitigating manual processes. Data streaming allows data to be ingested from multiple systems, which can build a single source of trust for analytical systems. Additionally, these practices limit data branching and siloes, which can cause issues with data availability, quality and hygiene.
Data hygiene and security enable transformative benefits
Data hygiene is imperative, particularly when striving to ethically and accurately utilize data for an autonomous system like AI or ML. A robust data validation framework is necessary to improve data quality. To create this framework, agencies can map their data’s source systems and determine the types of data they expect to yield, but mapping becomes increasingly arduous as databases continue to scale.
One critical success factor is to understand the nature of the data and the necessary validations prior to ingesting the data into source systems. Hygiene can be improved by consuming the raw data into a data lake and then, during conversion, validate the data’s quality before applying any analytics or crafting insights.
In addition to data hygiene, data security must remain a top priority across the federal government as agencies move toward real-time data insights. Adopting a hybrid, multi-cloud environment can lead to a stronger security posture because there are data encryption capabilities inherent in enterprise cloud environments.
Agencies may consider using a maturity model to help their teams assess data readiness and how they are progressing in their cybersecurity frameworks. A maturity model lets agencies identify and understand specific security gaps at each level of the model and provides a roadmap to address these gaps. Ultimately, the cybersecurity framework is as essential as data hygiene to ensure agencies can harness data reliably and efficiently.
When agencies have data management solutions that reduce the friction of navigating siloed government systems and enable faster, more secure collaboration, it enables them to drive innovation. This is especially true for agencies that handle extensive amounts of data. For example, many High Impact Service Providers (HISPs) must manage vast amounts of citizen data to provide critical, public-facing services with speed and scale.
Data is the foundation for modern digital government services. Once data is ingested, stored and secured effectively, the transformational potential of emerging technologies such as AI or RPA can be unlocked. Moreover, with real-time data insights, government decision-makers can use actionable intelligence to improve federal services. It’s essential that agency IT leaders invest in a robust data management strategy and modern data tools to ensure they can make informed decisions and benefit from the power of AI to achieve mission-critical outcomes for the American public.
Joe Jeter is senior vice president of federal technology at Maximus.
Robust data management is key to harnessing the power of emerging technologies
Comprehensive data management is key to unlocking seamless, personalized and secure CX for government agencies.
The recent AI Executive Order aptly states that AI reflects the data upon which it is built. Federal agencies are looking to responsibly implement cutting-edge IT innovations such as artificial intelligence, machine learning and robotic process automation to improve customer experiences, bolster cybersecurity and advance mission outcomes. Accessing real-time, actionable data is vital to achieving these essential objectives.
Comprehensive data management is key to unlocking seamless, personalized and secure CX for government agencies. Real-time data empowers informed, rapid decision-making, which can improve critical, high-impact federal services where time is of the essence, such as in response to a natural disaster. Alarmingly, only 13% of federal agency leaders report having access to real-time data, and 73% feel they must do more to leverage the full value of data across their agency.
While some agencies are making progress in their IT modernization journeys, they continue to struggle when it comes to quickly accessing the right data due to numerous factors, from ineffective IT infrastructure to internal cultural barriers.
Actionable intelligence is paramount. The ultimate goal is to access the right data at the right moment to generate insights at “the speed of relevance,” as leaders at the Defense Department would say. To achieve the speed of relevance required to make real-time, data-driven decisions, agencies can take steps to enable quicker access to data, improve their data hygiene, and secure their data.
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How to effectively intake and store troves of data
From a data infrastructure perspective, the best path to modernized, real-time deployment is using hyper automation and DevSecOps on cloud infrastructures. Many federal agencies have begun this transition from on-premises to cloud environments, but there’s still a long way to go until this transition is complete government-wide.
Implementing a hybrid, multi-cloud environment offers agencies a secure and cost-effective operating model to propel their data initiatives forward. By embracing standardization and employing cloud-agnostic tools for automation, visibility can be enhanced across systems and environments, while simultaneously adhering to service-level agreements and ensuring the reliability of data platforms. Once a robust infrastructure is in place to store and analyze data, agencies can turn their attention to data ingestion tools.
Despite many agency IT leaders utilizing data ingestion tools such as data lakes and warehouses, silos persist. Agencies can address this interoperability challenge by prioritizing flexible, scalable and holistic data ingestion tools such as data mesh. Data mesh tools, which foster a decentralized data management architecture to improve accessibility, can enable agency decision-makers to capitalize on the full spectrum of available data, while still accommodating unique agency requirements.
To ensure data is accessible to decision-makers, it’s important that the data ingestion mechanism has as many connectors as possible to all sources of data that an agency identifies. Data streaming and data pipelines can also enable real-time insights and facilitate faster decision-making by mitigating manual processes. Data streaming allows data to be ingested from multiple systems, which can build a single source of trust for analytical systems. Additionally, these practices limit data branching and siloes, which can cause issues with data availability, quality and hygiene.
Data hygiene and security enable transformative benefits
Data hygiene is imperative, particularly when striving to ethically and accurately utilize data for an autonomous system like AI or ML. A robust data validation framework is necessary to improve data quality. To create this framework, agencies can map their data’s source systems and determine the types of data they expect to yield, but mapping becomes increasingly arduous as databases continue to scale.
One critical success factor is to understand the nature of the data and the necessary validations prior to ingesting the data into source systems. Hygiene can be improved by consuming the raw data into a data lake and then, during conversion, validate the data’s quality before applying any analytics or crafting insights.
In addition to data hygiene, data security must remain a top priority across the federal government as agencies move toward real-time data insights. Adopting a hybrid, multi-cloud environment can lead to a stronger security posture because there are data encryption capabilities inherent in enterprise cloud environments.
Agencies may consider using a maturity model to help their teams assess data readiness and how they are progressing in their cybersecurity frameworks. A maturity model lets agencies identify and understand specific security gaps at each level of the model and provides a roadmap to address these gaps. Ultimately, the cybersecurity framework is as essential as data hygiene to ensure agencies can harness data reliably and efficiently.
Read more: Commentary
When agencies have data management solutions that reduce the friction of navigating siloed government systems and enable faster, more secure collaboration, it enables them to drive innovation. This is especially true for agencies that handle extensive amounts of data. For example, many High Impact Service Providers (HISPs) must manage vast amounts of citizen data to provide critical, public-facing services with speed and scale.
Data is the foundation for modern digital government services. Once data is ingested, stored and secured effectively, the transformational potential of emerging technologies such as AI or RPA can be unlocked. Moreover, with real-time data insights, government decision-makers can use actionable intelligence to improve federal services. It’s essential that agency IT leaders invest in a robust data management strategy and modern data tools to ensure they can make informed decisions and benefit from the power of AI to achieve mission-critical outcomes for the American public.
Joe Jeter is senior vice president of federal technology at Maximus.
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