Success on the battlefield and in the boardroom isn’t about more data. It’s about rapid insights from data.
We deploy cloud technologies, open-source software, and big-data engineering solutions all to help you extract the most relevant information—from across the data landscape—for the greatest impact.
SAIC provides cost, resource, and process efficiencies through a number of solutions:
- Applications designed to efficiently and smoothly collect, archive, display, transform, and process large structured and unstructured volumes of data.
- Cloud-based strategies to provide access to data no matter where it resides inside or outside the organization.
- Analytics suites that contain automated capabilities, an open architecture, and a standards-based framework necessary to support activity-based intelligence.
- Dynamic capabilities that enable data integration from across the enterprise without the need for a lengthy and costly rigid data warehouse integration.
A Long History of Integrating Data for Stellar Search Performance
Learn how SAIC reduced the response time for queries to the National Archive and Records Administration (NARA) from up to two weeks to less than three seconds.
Info When It's Needed, at a Lower Cost.
Big data must be fast data. With real-time access to mission-critical intelligence, decision-makers can take advantage of growth opportunities, obtain valuable insights, and address issues as they occur. Investments in our big data analytics solutions leverage emerging open-source capabilities that provide managers with a range and depth of information from across the enterprise, agency, or external sources at reduced costs and greater speed. SAIC’s big data engineering solutions permit data scientists to forgo the reformatting and refinement process of conventional data management and use raw data in a variety of structures from multiple internal and external sources to derive powerful, actionable insights more quickly.
Use Data from the Cloud as Performance Needs Dictate.
Cloud computing has revolutionized the management of large data sets. Big data environments rely on clusters of servers to support the tools and technologies that bring large volumes of data to life. Clouds pool server, storage, and networking resources in order to scale up or down as needed. Our cloud computing gives organizations an efficient and flexible way to access as much or as little data as necessary to accomplish tasks of all sizes from intermittent, ad-hoc analyses to advanced analytics applications.
Pool Data Assets from Across Departments or Other Agencies.
Traditional data warehousing practices are fraught with limitations, such as their inflexibility to handle new data or new analysis needs, or their lengthy time-to-value and the associated costs. A new information architecture makes use of metadata, data virtualization, and distributed processing to enable automated enterprise analytics. With SAIC’s logical data warehousing approach, even siloed data can be shared across departments or agencies, delivering maximum value to the organization and unlocking the potential of big data.
Big data solutions for real-world challenges.
SAIC has developed a wide range of products and services that address the most perplexing problems in government and private enterprise and leverage the company’s heritage, world-class talent, and expertise in data engineering, analysis, cloud technologies, and open-source software environments.
When daily operational data is your company’s lifeblood, trust SAIC to manage it.
SAIC builds data systems that cover the full data-processing lifecycle, from raw data to phenomenology. Activities run the full spectrum from developing data production requirements to the design, development, testing, and operation of the systems. We provide operational data processing and archiving support to both enterprise customers and government agencies.
SAIC offers the operational data-processing experience that you require to help you compete on a global scale. We develop, integrate, and test software systems for the operational and real-time use in an enterprise setting. We also build applications, such as onboard processing and control, ground system operations and management, and system data processing and evaluation that can support the needs of DoD, NASA, NOAA, and other agencies and organizations.
- Incorporate business and mission intelligence into operational decision-making processes to optimize your organization’s performance.
- Capture and respond to operational data more quickly to increase your advantage.
- Expertise in reengineering, data services, relational database design and integration, and distributed systems.
- Leadership in the development of data systems that support global change monitoring and meteorological research.
Make your decisions better, faster, and smarter with SAIC’s data warehousing strategies.
SAIC’s data access layer allows you perform analytics across multiple data silos, without having to integrate the data into one monolithic platform. Historically, this has been a costly, time-consuming process that could take years to yield results and also cannot be easily changed whenever new data sources are added or new analytics are needed.
Our approach to data warehousing provides access to data assets from flat files, data marts, data warehouses, or external data sources that you may not own or control to advance your real-time decision-making processes.
- Add big data capabilities incrementally.
- Reuse rather than replace existing assets.
- Maintain analytics capabilities for users while underlying systems are modernized.
- Adjust query capability—known as schema-on-read—dynamically as needs change.
Turn widespread data assets into tangible benefits to your enterprise.
It is critical to know what data assets you have, where they are, their collection history, and what the data elements mean. Only with an enterprise-wide view of your data can you derive enterprise-wide benefits.
- Gain the ability to use data across the enterprise.
- Standardize processes for data retention and data quality.
- Create an enterprise-wide governance strategy.
- Expertise in enterprise architecture that enables the use of data across the enterprise
- Expertise in semantic data description and data dictionaries
- Created a data stewardship program
- Designed a content governance process
- Identified and documented data quality issues
Reduce logistics costs and optimize customer outcomes.
Logistics information systems and related technologies play an essential role in reducing costs and optimizing the performance of the logistics enterprise. Our technology solutions enable efficient management and support of platform or system fleets by simultaneously tracking location, configuration, and condition. Our enterprise distribution and asset visibility solutions optimally trade inventory and transportation costs to get the right parts to the right place at the right time.
A sampling of our offerings includes: total asset visibility and management; enterprise data integration and management; demand forecasting and inventory optimization; automatic identification technology and data capture; logistics systems development, deployment, and sustainment; and data analytics, predictive modeling, and decision support.
Bring the power of your entire enterprise data together.
With ever-shrinking budgets and ever-growing demands for data visualization and analytics, SAIC provides you with a big data platform that allows for rapid enterprise-wide analytics across disparate data silos. You can incrementally add big data capabilities to your current analytics infrastructure and quickly gain actionable insight. The Logical Data Analytics Solutions (LDAS) leverages state-of-the-art data science technologies with scalability to handle the volume and variety of big data. LDAS provides enterprise or inter-enterprise analytics with lower cost and more rapid time to value.
- Rapid time to value through dynamic integration across existing sources
- Enterprise analytics without the expense of a new enterprise data warehouse by leveraging existing storage repositories
- Can be deployed on commodity boxes using data center or cloud
- Near-linear scalability
- Dynamically encompasses sources outside the agency
- Flexibility in doing new types of discovery analytics
- Open-source ochestration avoids costly licensing feeds to do more with less
- Automated data integration and long-term stewardship and visibility into all data assets provides for scalable semantic metadata layer
- Data-layer security assurance
- Flexibiilty to span hybrid environments
- Our credentials and expertise with big data enables your analysts to focus on analyzing enterprise data, rather than spending time hunting, copying, and managing data.
- We use an established open-source process to pull data dynamically from sources or stage data in repository for better performance.
- Built-in elements for analytic flexibility and scalability.
- Easy use for browsing, visual exploration, retrieval, and analysis.
Big data. Powerful impact.
EPA Climate Change
SAIC mounted a greenhouse gas analytics effort to identify outliers, data quality, and mission trends. The firm developed a system using open-source tools, Kettle ETL, Mondrian OLAP, and Spago BI to ensure the quality of data prior to public release. The solution generated critical metrics to verify that policies, emission reduction investments, and emission trends were based on sound observations.
USDA Public Health Information System
SAIC developed a comprehensive predictive analytics software suite for risk assessment, alerting, machine learning, and reporting for the Food Safety Inspection Service. The company utilized SAS, Business Objects, and Google visualization to develop an integrated source of data for risk assessment, prediction, and management of potential issues related to public health.
Department of Defense, Deputy Chief Management Office
SAIC designed and built a federated information warehouse by implementing Apache Tomcat, Java, Oracle, Tableau, Ab-Initio, and standard DoD IT security and Information. The system enabled the automation of many elements of the Investment Review Board process, which resulted in reduced review cycle times, decreased staff and improved investment data integration and quality.
Defense Enterprise Computing Center
The Defense Enterprise Computing Center (DECC-M) is fully integrated with 13 DECC contiguous U.S. locations and supports more than 1.25 million globally dispersed customers. It encompasses DoD component agencies, the State Department, and other government/non-governmental agencies. SAIC has supported all aspects of the enterprise data warehouse needs for the Defense Enterprise Computing Center in Montgomery, AL. SAIC tasking includes EDW design, implementation and configuration management, 24x7x365 operational support, and the management of all data center resources.