Data Readiness, Analytics and Management

Modernize your data intelligence by developing a data management strategy to drive better analytics and governance across your enterprise.

Advancing Data Management is important when users and management are relying on quality, trusted, secure data that is governed and well managed for analytics and visualizations and for AI/ML developers and data analysts and scientists to trust for business intelligence and new technology.

Workflow Automation is key to improve efficiency as data volumes increase and data preparation processes are manual and become more complex.

New technologies, processes and practices will help organizations stay current on data governance and quality challenges as they seek to turn unknown data sources into vital resources for innovation.

Standard Approaches

• Advance data readiness by developing knowledge graphs of data relationships.
• Establish a data catalog to improve location, analysis, and governance of data.
• Address weaknesses in governance that impact readiness and reduce data trust
• Improve readiness through efficient, flexible, and integrated data preparation
• Modernize pipelines for analytics and AI/ML with catalogs and workflow automation