Data Governance is the combination of three dimensions: individuals, processes, technologies - that work together to ensure business can safeguard their data, control who is responsible for owning and managing it, and distribute it to employees for routine use.

There is no point of focusing on software/technology only - if there are no people or team that does rigorous maintenance of the data estate. Similarly, there is no value in technology and people - if there is no workflow mechanism that can help adding more data and more roles in the framework. 

Process Automation ensures all dimensions are included in the Data Governance.

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Finally, on the software side, real value in Data Governance is inter-relating all important SW pillars and not focusing on only one or two of them. Some of the pillars are: Data Quality, Metadata Management, Data Stewardship, Data Lifecycle Management, Data Security. 

However, beside data management pillars, Process Automation, Integration/Services Bus, API Management need to be added on application services side - for Full Lifecycle Data Governance - when it comes to Technology and Software use.

The more data is used without proper governance on application services and processes side without proper data level governance - the more data related risks and unrealised potential is there. The more data governance without application services governance input on data - the highest is the multiplier for poor data integrity

Process Automation is the crucial central component for proper strategy on Full Lifecycle Governance in interoperability between multiple pillars of the stack.

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Some of the DG tools that are visualised in this session are: Oracle Process Automation, Oracle Integration Cloud, Oracle API Gateway, Oracle Data Quality, OCI Data Integration, OCI Data Catalog, Oracle Enterprise Metadata Management

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