The management of master data is also called Master Data Management. Examples of another entity like a product: name, description, category. Examples of master data for a contact: first name, last name, address, gender. Master data summarizes data that is necessary for the regular processing of a record and does not change frequently. The focus is first on master data, which is merged and consolidated. CRM, ERP, e-commerce, marketing automation), then each system shows only an incomplete view of the theoretically available data. If customer data is distributed across many systems (e.g. The Golden Record brings together the available data of an entity (e.g. This is inseparably linked to a Customer Data Platform. with the Marini Integration Platform, then we face the next challenge: the creation of the golden record. If we now assume that the integration has been realized, e.g. We’ll leave aside the fact that it’s often the pulling together (the integration) that fails. I simply pull together all the information about a customer, store it, and provide a visualization of the data – whether chart or table wise.
#Golden records management system professional
Academy Learn in-depth skills for professional and successful data management from experts.Comparisons Compare enterprise data integration solution providers and find the right one for your business.Trust Center Non-compromising at its core: secure and stable operation, high-performance processing, data protection-compliant.Why Marini Systems? Trust in a company that works in partnership with you to find and implement the best possible solution for you.Industries Our platform is designed to meet your industry-specific requirements.Applications Depending on your requirements, you can employ our platform and its components for a variety of purposes.Integrations Learn more about what characterizes the integration of the most popular enterprise applications and systems.Support We support you with everything concerning your platform – with extensions or all other questions.Projects We plan and implement your integration projects together with you, step by step, successfully and sustainably.Consulting We support you in the long term with your digital strategy and realize your platform together with you.Data Marketplace Increase your data quality via external sources and boost your success with better data.DataEngine The DataEngine specializes in data management and especially ETL – all data and processes.HubEngine The HubEngine specializes in unlimited data exchange via APIs – all endpoints and methods.Centralized Data Management Integrate your systems with a central platform (EDP, CDP) and gain a central view of your customers.Thus, you obtain consistent and current data in all systems. Distributed Data Management Integrate your systems into a distributed platform.
Integration Workflows Connect your systems without limitations in real time and control your automated processes across systems.
Rapid implementation of a CDH solution with high scalability and targeted behavior of data will generate a positive return on investment (ROI). This reduces costs, while at keeping the project itself lean and the project risk calculable. Based upon the principles of lean integration, this approach enables fast presentation of operatively pertinent results and gradual incorporation of further customer data into your CDH solution. The Customer Data Hub does not require complex integration projects or changes to currently existing data models.
#Golden records management system software
From within the framework of an established data governance initiative, you can coordinate and control a powerful master data management based upon reliable customer master data.Īnchor’s CDH solution means that exhaustive programming, adaptation, and time-consuming software maintenance are no longer needed. Appropriate rights for the respective user are allocated, setting out who can read, add, and alter differing types of data from different sources. Once a sufficient data quality level has been achieved, it can be easily maintained for the future. Any changes made to the master data are clearly visible and can be understood. For example, master datasets can be merged and master data reinstated with original elements (“unmerged”), and relationships and hierarchies can be shown. Web-based data stewardship interfaces help define and administer appropriate sets of rules, guidelines, work-flows, and processes within the framework of data governance.
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