At BigBear.ai, we aren’t constrained by the status quo or technical limitations. We think outside the box to arrive at solutions that previously weren’t possible. Our customers and partners bring us their most difficult business problems because they know we never back down from a challenge. We like being known for pushing the limits and achieving success where others have failed.
We work with our clients to understand their data – where it comes from, who owns it, the rules that act upon it, who needs it and much, much more. We then work to develop a data migration plan that results in the cleanest data possible stored in the right repository for data analysis.
We also help our clients form governing bodies as well as data management policies and procedures to ensure that once their data is cleansed, it stays that way.
With an understanding of our clients’ data goals and needs, we work to develop a data architecture optimized to meet organizational needs.
Our architectures address all aspects of data management – from processing and storing data to hardware, software, and data models customized to client needs.
Operational Data Store
We create central repositories that combine data from multiple transactional systems to provide a snapshot of the latest data to be used for operational reporting, freeing your transactional systems to focus on serving your customers. Our Operational Data Store designs can also help your company integrate applications through data instead of via complicated code integrations.
We design Enterprise Data Warehouses to allow the strategic thinkers of an organization to quickly consume and make informed decisions based on the information derived from data contained in the tactical systems of the enterprise as well as from external sources.
We turn data into intelligence for government and business leaders. We work with these leaders to define the key performance metrics they need to measure success. With this knowledge, we develop methods to assemble, present and disseminate the information to organizational stakeholders in a way that makes sense to them in managing their business.
We implement and curate large repositories of structured and unstructured data for the enterprise to be used for reporting, visualization, analytics and machine learning.
Finding relationships, patterns and trends is cumbersome when dealing with large datasets. Our exploratory analytics team uses data mining and other methods to examine previously unknown information about our customers’ data to arrive at new insights.
Imagine what you could achieve if you could predict future events. Imagination becomes reality with predictive analytics. Our team of experts uses a combination of technologies and cross-validation methods to break through the noise in big data, pinpoint important variables, and deliver accurate predictions of operational outcomes based on validation data.
Sometimes seeing the relationships and patterns in data is difficult to see in standard data schemas and database tables. That’s where our visualization team comes in. We develop software that brings the “data to life” by displaying it visually; thereby, making it easier for clients to understand the story their data is telling.
At BigBear.ai, we developed the Artemis Anticipatory Network (A2N) to take standard machine learning to the next level. Our solution helps leaders outmaneuver opponents. A2N learns relationships across domains with modern machine learning and then forecasts behaviors, detects anomalies and predicts the likely impacts of decisions. A2N also addresses the shortcoming of most other artificial intelligence solutions – it is able to process data in its native form. Dirty data isn’t a problem for our solution because we built it to leverage the tensor completion algorithm, making it more viable in the real-world where imperfect data is the norm, not the outlier.
BigBear.ai has expertise in both Amazon Web Services and Microsoft Azure cloud platforms. We can help you move from on-premises to a hybrid to a full cloud environment.
We provide the expertise necessary to realize the availability, reliability and scalability of cloud computing environments.
Decision Dominance for Decisive Advantages