- Posted by admin
- On June 23, 2016
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- master data management, MDM
In business, master data management (MDM) comprises the processes, governance, policies, standards and tools that consistently define and manage the critical data of an organization to provide a single point of reference.
Master data management (MDM) is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets.
Recently, there has been an emphasis on regulatory compliance. Mergers and acquisitions are also becoming common. Hence it has become imperative to create and maintain master data in any business organization. Master Data is common data about customers, suppliers, partners, products, materials, accounts and other critical entities that is commonly stored and replicated across IT systems. Master Data is the high-value, core information used to support critical business processes across the enterprise. Master data is the crucial data in a business organization. Master data consists of lists of data that is shared by several applications that make up the system. It consists of a customer master, an item master and accounts master.
There are 5 types of master data
- Unstructured data: This is obtained from e-mails, whitepapers, magazine articles internet portals and PDF files.
- Transactional data: It is related to sales, bills, deliveries, claims and other monetary and non-monetary transactions.
- Meta data – Meta data is data about data. It exists in XML document form, reports, log files or configuration files.
- Hierarchical data – It stores the relationships between different forms of data. It is very critical to business and is considered to be super data because it in discovering relationships in master data.
- Master data: It consists of 4 groups – people, places, things and concepts. The 4 groups contain further sub groups; for example people may be employees, managers or customers. Things may refer to product or asset. Concepts include warantee, contracts or licenses.
Master data management ( MDM)
MDM implies the technology, tools and processes required to create and maintain lists of master data. MDM is more than just technology; creating clean data is not enough. The solution must include tools and processes to maintain the clean data consistently as it is expanded and updated periodically.
A master data management plan should be based on requirements, priorities, available resources, time frame and nature of the problem. The Master Data Management plan consists of the following steps:
- The first step is identification of the sources of master data. This step proves to be full of surprises. A company may suddenly discover customer databases that it did not know about.
- After the sources are identified, the next step is to decide the producers and users of master data. This step is redundant if the producers and users are clarified in the first step.
- Next task is to collect and analyse metadata about the data. It includes attribute name, data type, constraints, dependencies etc. this step may be complicated if you have to start from scratch.
- The next move will be to appoint staff who has knowledge about the current source of data and the skill to convert source into master data.
- Appoint a governing council. The representatives must have authority and power to decide how the master data is to be maintained, how to authorize changes and how long it should be preserved.
- Now develop a master data model. Decide how it will look, the data-type, values allotted and so on. Design a simple and good looking model. It should not be complex and confusing.
- Choose a tool-set. You will need to buy or build tools to create the master lists by cleaning, transforming, and merging the source data. You will also need an infrastructure to use and maintain the master list. The techniques to clean and merge data are different for different types of data, so there are not a lot of tools that span the whole range of master data.
The two main categories of tools are Customer Data Integration (CDI) tools for creating the customer master and Product Information Management (PIM) tools for creating the product master.
- Design an infrastructure. Reliability and scalability are important considerations in the design.
- Generate the master data and test it. You will have to use your tools in this step. Check that the results are correct. If you find too many mismatches, the whole effort is wasted. Moreover it may land you in trouble later.
- Modify the system based on the test results. You may have to make some changes. Implement maintenance processes as well.
Thus, you can observe that Master Data Management is a long and complex process that can continue for a long time. Whenever new software is introduced, the best practice is to proceed step-by-step, in chunks. Break up the entire process into smaller units and implement one at a time. The next will be based on the success and benefits of the previous one. Handling the entire project at a time can become unmanageable and baffling. Take the support of IT professionals.
MDM is crucial to a business enterprise. A single trifle error can be dangerous. For example, if the customer’s address is wrong, the delivery will be made to a wrong person, the bills will go to a wrong address and there will be confusion. MDM offers clear and concise understanding of data pertaining to customers, products, partners, suppliers, locations, assets, liabilities or other items.
Master Data Management is important because it offers the enterprise a single version of the truth. Without a clearly defined master data, the enterprise runs the risk of having multiple copies of data that are inconsistent with one another. MDM is more important in larger organizations. The bigger the organization, the more important MDM is, because a bigger organization means that there are more disparate systems within the company, resulting in difficulty in providing a single source of truth.
Many companies grow through mergers and acquisitions. Each company comes with its own set of master data. When the companies merge, the data also has to be incorporated. If the master data contains errors, they will be carried forward to the merged data. Hence phone numbers names, nicknames, spellings, addresses codes etc. have to be scrutinized carefully in master data lists.
iTivia technologies has expertise in key Master Data Management patterns and best practices in MDM. We provide a simple and trusted view of your data.