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Master Data Management - How Smart Companies Manage their Data

Big data is a resource that helps organizations to understand and take control or corrective action to address problems such as customer-centric service delivery, by accurately joining big data with Master Data Management (MDM) system. This helps the organizations to increase the level of trust in the information they use to make critical business decisions. IBM Info Sphere product which tries to resolve the organization needs using Info Sphere with MDM. Master Data adds strategic value to big data in mobile communication using IBM Info Sphere. Many mobile companies started using Master Data for analytical processing. One of such company is Philippines Telecommunication Company. It uses IBM Info Sphere to stream for Real Time Analytical Processing (RTAP). Big Data needs to be linked or related existing customer information already captured in traditional structured applications. Without linking it back to your master data, it ends up being another silo of data. This is due to the sum of the data in the individual systems is not accurately depicted with the whole of the business.

MDM helps to control the momentum of incoming data and tools that applied in MDM helps to verify facts about customers, vendors and products. Data definitions and rules that have been agreed to across your organization are now reflected in your MDM system. Organization uses the data to improve business operations, processes and decisions. For this, organization ensures that data is available across all operational systems. Service Oriented Architecture (SOA) plays a key role in helping companies to achieve the vision due to its agility nature. When new data and information integrated into the master data repository proper data governance policies and procedures will ensure continuous data excellence. However, integrating and consolidating data alone will not accomplish the objectives of organization, the true value is seen only when the consolidated master data is integrated back into the operational and analytical use by the participating application, allowing the enterprise to have a single, synchronized view of its business data. For this, service-oriented architecture is required.

In essence, there is a symbiotic relationship between data governance and SOA. SOA is centered on providing consistent services across applications. For the proactive organization, this means making sure that data is manipulated via the services layered on top of the MDM system, providing a consistent set of services. For example, there needs to be a service that will “determine if a customer is a new customer”. This service should be deployed in all operational and analytic applications so that all systems run the same service. This will prevent finance or distribution from adding a new customer that already exists in a sales force automation or marketing system. The success of data governance depends on the ability to deploy and use Master data and manipulation services. At the same time service-oriented approach to business solution development relies on the existence of a governed master data repository. When the consistent data services and the master data are deployed across the enterprise, it will truly have enterprise consistency. SOA is rapidly becoming the architectural foundation in most organizations.

Risk Mitigation is the important reason for a company to pay attention to the data quality. Master Data Management motivates customers to match their unstructured data with their master data and it supports large transaction loads and high availability operational environments. Unstructured data requires more Data Base facility. Configuration to handle such requirements can be managed by the large organization. Data quality and Data governance should never be considered as a one-time project. Better data leads to better decision which ultimately leads to better business. Combining the power of Big Data with MDM creates a valuable connection. The capacity to analyze large volumes of stored data at rest and the ability to discover new pattern alone will not help the organization to optimize the existing redundant process and increase the profitability.

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