Data Science: Predicitive Data Analytics (AI/ML) & Data Visualization

Data Science: Predicitive Data Analytics (AI/ML) & Data Visualization

The integration of data from the edge to the enterprise level is crucial in facilitating informed decision-making.

Implementing a design that incorporates data orchestration, and data fabric or data mesh, ensures effective enterprise data management and governance. Such a design, enhanced with DevSecOps pipelines and environments, allows for optimized data placement, both in compute and store design. Furthermore, the use of big data platforms or data repositories not only ensures cybersecurity assessment and authorization but also allows for system administration and the development and integration of deployable analytics. The testing, hardening, and integration of data and AI/ML tools are essential steps, along with the development and integration of functional AI/ML algorithms. Incorporating Data for Influence into operations or intelligence, specifically utilizing Publicly Available Information and Commercially Available Information, can provide an additional layer of insight. Finally, the visualization of data and the integration of a multi-domain Common Operating Picture (COP) can enhance overall comprehension and operational efficiency.