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Dan Power highlights the importance of having a Model-driven MDM to succeed in Data Management and Data Governance
Dan Power highlights the importance of having a Model-driven MDM to succeed in Data Management and Data Governance
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A Model-Driven Approach and Proactive Data Governance Deliver Multidomain MDM Today.
The combination of the model-driven approach and proactive data governance frees the business up from the constraints of customer- and product-centric hubs. Since you can model any data structure, you’re not limited to the pre-established tables and columns that the software vendor built into the data model. Once you get used to this freedom, you’ll never want to go back to a rigid, pre-built data model again. The model-driven approach also gives the ability to leverage your existing assets by re-using data models from both internal and external sources, including available industry standards.
The whole intent of proactive data governance is to put the business in the driver’s seat. Between the flexible data modeling, collaborative user interfaces, easy-to-use hierarchy management, advanced version control, built-in workflow, role-based security, productivity features, and the middleware integration, the business becomes an equal partner of IT. Since master data management programs tend to be more successful when business people are actively engaged from the very beginning, having the business participate on an equal footing with IT is a huge step forward. The business team can participate in the project, and the IT team can concentrate on the challenging technical parts of the project that involve middleware, data quality, databases, performance engineering, testing, etc.
According to “Software Maintenance” by Gerardo Canfora and Aniello Cimitile, “software maintenance consumes 60% to 80% of the total life cycle costs”. So for every $1 spent on initial development, roughly $4 in maintenance costs is incurred over the lifetime of the application. Having the business participate in the maintenance of the MDM and data governance platform dramatically reduces IT costs. And multidomain MDM is needed to solve the most challenging business problems. For example: when you are tracking physician spending in the pharmaceutical industry, you’re usually pulling in many different types of master data: product (different types of drugs and devices), internal parties (employees, i.e., salespeople working with different physicians), external parties (healthcare providers, i.e., physicians), locations (states to which you have to report spending), etc.
So a customer-centric or product-centric MDM platform can quickly become a problem. Either the software vendor will do or has already done the customization needed, or you’ll have to. Solving today’s business problems can require data from as many as seventy different domains of data. But the model-driven approach we’ve discussed here, combined with the proactive style of data governance we’ve discussed elsewhere, delivers multidomain MDM today. The model-driven approach allows all domains of data to be incorporated into the MDM hub’s data model on an equal basis. And the proactive data governance model includes the business in the entire MDM life cycle, so business owners, end users and data stewards are involved in every step of solving the tough business problems using the data governance platform.
By Dan Power, member of the MAG
The combination of the model-driven approach and proactive data governance frees the business up from the constraints of customer- and product-centric hubs. Since you can model any data structure, you’re not limited to the pre-established tables and columns that the software vendor built into the data model. Once you get used to this freedom, you’ll never want to go back to a rigid, pre-built data model again. The model-driven approach also gives the ability to leverage your existing assets by re-using data models from both internal and external sources, including available industry standards.
The whole intent of proactive data governance is to put the business in the driver’s seat. Between the flexible data modeling, collaborative user interfaces, easy-to-use hierarchy management, advanced version control, built-in workflow, role-based security, productivity features, and the middleware integration, the business becomes an equal partner of IT. Since master data management programs tend to be more successful when business people are actively engaged from the very beginning, having the business participate on an equal footing with IT is a huge step forward. The business team can participate in the project, and the IT team can concentrate on the challenging technical parts of the project that involve middleware, data quality, databases, performance engineering, testing, etc.
According to “Software Maintenance” by Gerardo Canfora and Aniello Cimitile, “software maintenance consumes 60% to 80% of the total life cycle costs”. So for every $1 spent on initial development, roughly $4 in maintenance costs is incurred over the lifetime of the application. Having the business participate in the maintenance of the MDM and data governance platform dramatically reduces IT costs. And multidomain MDM is needed to solve the most challenging business problems. For example: when you are tracking physician spending in the pharmaceutical industry, you’re usually pulling in many different types of master data: product (different types of drugs and devices), internal parties (employees, i.e., salespeople working with different physicians), external parties (healthcare providers, i.e., physicians), locations (states to which you have to report spending), etc.
So a customer-centric or product-centric MDM platform can quickly become a problem. Either the software vendor will do or has already done the customization needed, or you’ll have to. Solving today’s business problems can require data from as many as seventy different domains of data. But the model-driven approach we’ve discussed here, combined with the proactive style of data governance we’ve discussed elsewhere, delivers multidomain MDM today. The model-driven approach allows all domains of data to be incorporated into the MDM hub’s data model on an equal basis. And the proactive data governance model includes the business in the entire MDM life cycle, so business owners, end users and data stewards are involved in every step of solving the tough business problems using the data governance platform.
By Dan Power, member of the MAG
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