Operationalize data and AI platform
Operationalize the data and AI platform and data science model means moving the data science models and analytical application into production. Also, this includes managing the models, overseeing the data platform/data pipes, and maintaining analytical business applications.
Steps for Operationalizing a Data and AI Platform
Operationalizing a data and AI platform involves taking a data and AI solution from development and testing to production and ongoing maintenance. Furthermore, this process ensures that the solution is reliable, scalable, and secure. Additionally, it can be effectively monitored and maintained over time
Operationalizing a data and AI platform involves taking a data and AI solution from development and testing to production and ongoing maintenance. Additionally, this ensures that the solution is reliable, scalable, and secure, and that it can be effectively monitored and maintained over time.
Data governance is important when operationalizing a data and AI platform because it establishes clear policies and procedures for managing data. Likewise, this also includes roles and responsibilities, data management and security processes, and standards and guidelines for data quality, compliance, and privacy. Additionally, to identify and address any issues in a timely manner.
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