Artificial Intelligence
Mathematica’s multidisciplinary teams have a wealth of experience in artificial intelligence (AI) techniques and methodologies, including all disciplines of machine learning and natural language processing. Our technical teams can help health care organizations in Arizona use and leverage AI to promote data-driven practices.
Geospatial Data Visualization
Mathematica’s expertise handling the unique complexities of geospatial data can help health care organizations in Arizona better understand spatial features in their data, and leverage those insights to promote a culture of data-driven decisions. We work with a variety of spatial data formats and have extensive experience geocoding and linking disparate data sources for predictive modeling. Our reproducible workflows and trainings for data management and analysis can help build local capacity for geospatial methods.
Data Solutioning
Mathematica brings decades of methodological experience and broad, substantive expertise to the data collection and data solution process. We have engaged partners across health, criminal justice, economic development, and employment sectors to promote collaboration and information sharing. We do this by implementing data systems that help our partners identify and target resources to the most vulnerable populations with the greatest needs.
Our data consulting is rooted in research. Our data analysts that once primarily supported internal research and evaluation projects now provided dedicated data management solutions to health care organizations. Our data analysts that once primarily supported internal research and evaluation projects now provide dedicated data management solutions to health care organizations.
Data Management and Governance
Our data management and governance solution empowers health care organizations to:
- Align business practices with data to ensure that data produced and consumed are known throughout the organization
- Identify and catalog numerous data sets and manage a high volume of data
- Develop and use processes to meet quality standards
- Assess the completeness of the data and their readiness for use
- Execute governance and management processes to preserve data quality over time and provide a scalable framework for improving data quality