A lot of companies nowadays, especially global businesses, own a really huge number of applications and systems in which data flowing through departments and divisions would be fragmented, duplicated as well as outdated. If this takes place, giving answers to the most basic to more important questions about any kind of performance KPI for a company would be a big problem.
Some of those questions would be who your most profitable clients are, what products come with the best margins or simply how many employees your company has and so on.
The requirement for accurate and timely information is always in need and because sources of data increase, taking control over it in a consistent manner and keeping it updated for a whole business to use the same information have always been a big difficult.
In order to meet these difficulties, businesses take advantage of master data management. Before moving to the definition of master data, there are 6 types of data that you need to know. First of all, unstructured data is the one found in email, white papers as well as magazines, intranet portals, product information and PDF files. Transactional data is data regarding business events, which is often referred to system transactions such as sales, deliveries, invoices, tickets, claims and so on that are needed to be analyzed by other systems. Transactional data are unit level transactions utilizing master data entities.
Next, metadata means other data. It may locate in a formal repository or in different forms including XML documents, report definitions, descriptions in a database, log files, connections and configuration documents.
Hierarchical data is the data keeping the relationships between other data. It would be saved as a part of an accounting system or independently as descriptions of relationships in real work, like company organizational structures or product lines. Hierarchical data is taken into consideration as a super master data management domain as it is important to understand and discover the relations between master data.
Reference data is another special type of master data which is utilized to clarify other data or used to connect data to information out of the boundaries of the company. Reference data could be shared throughout master or transactional objects, such as countries, currencies, time zones, and so on.
Last but not least, master data is the major data in the company describing objects around which business is carried out. It will not change in a frequent manner and can come with reference data which is not needed to run the business. Actually, master data is not a transactional type, yet it makes description for transactions. The critical nouns of an enterprise that are covered by master data have four domains and other categorizations in those domains are named as subject areas, sub-domains and entity types.
Enterprise data management is the process in which your business data is inventoried and governed while your organization can get on board with the process. It means that Enterprise Data Management refers the way to manage people as it is about managing data.
Data management means guaranteeing that your people have the accurate data they need on time and they also follow the standards to store quality data in a standardized, secure and governed location. The following sections are the quick instruction of the most commonly asked questions about enterprise data management that you can learn more.
Who will take the responsibility of enterprise data management and what should they do?
Enterprise data managers relate to database admins, IT admins or IT project managers. They will take the responsibility of managing your business data life cycle. Also, they will document and direct the flow of data starting from ingestion stage, then they take control over the process of eliminating the data that the business does not need. This life cycle also means a data lineage.
By managing your data lineage, your data will be more secure and can be better prevented from breaches, incorrect analysis and legal issues. The legal complications may turn up if you have insecure information no matter where they are located.
The advantages of enterprise data management
Through making data management a priority for your company, you are making sure that your data is located in a secure location and can be accessed when you are in need. This will help your teams be able to access high-quality to analyze correctly, make sure your data is safe and compliant to regulations, consolidate data throughout different sources for higher efficiency and have a consistent data architecture which is suitable for your company.
Data management solutions, such as Informatica, can support you with all the above tasks. Moreover, data analysis and other data jobs will be much more effective as your employees can know exactly where they could find the data they need. In addition, a well-governed data lineage can help identify data dependences easily and quickly, understand who is making use of each data source and so many other benefits.
Master data management versus enterprise data management
Master data management is rather identical to enterprise data management, yet it has building a single view of your data in a master file or master record. This master file will define the important points you need for every particular process. You can consider this as a requirement document in which there are necessary fields and inputs to your data source.
For instance, you can consider what your sales department is in need in order to store both leads and opportunities. To start, things that are needed would be names, phone numbers and email addresses. These fields would come from another tool and we will need to understand the relevant details. Another more sophisticated example of master data management is creating a master file with complicated categories and dimensions, such as providers in the supply chain, their location as well as reference data. This will rely on what business data your company is using in the process and what you want to take control over.