Master Data Management (MDM) refers to the process of creating and managing data that an organization must have as a single master copy, called the master data. Usually, master data can include customers, vendors, employees, and products, but can differ by different industries and even different companies within the same industry. MDM 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 typically more important in larger organizations. In fact, the bigger the organization, the more important the discipline of MDM is, because a bigger organization means that there are more disparate systems within the company, and the difficulty on providing a single source of truth, as well as the benefit of having master data, grows with each additional data source. A particularly big challenge to maintaining master data occurs when there is a merger/acquisition. Each of the organizations will have its own master data, and how to merge the two sets of data will be challenging. Let's take a look at the customer files: The two companies will likely have different unique identifiers for each customer. Addresses and phone numbers may not match. One may have a person's maiden name and the other the current last name. One may have a nickname (such as "Bill") and the other may have the full name (such as "William"). All these contribute to the difficulty in creating and maintain in a single set of master data.
Data classification is the categorization of data or categorizing of items in a logical and hierarchical order for its most effective and efficient use. This is the must exercise for every company to strengthen the roots of data as it plays the vital role of data protection throughout its lifetime.
Classification serves multiple purposes; if it is implemented effectively it gives better results on IT efforts towards data security and accessibility. This also helps in the development of chargeback model for storage.
Taxonomy is the hierarchical structure or the grouping of products according to the physical properties of the products to the taxonomy. Product taxonomy is based on its subclass hierarchy and is the best way to classify data. Taxonomies not only classify’s the products hierarchically but also helps in better organizing and understanding the products.
Building taxonomies requires the high discipline or knowledge of products both logical and physical properties. Hence it is done by a dedicated team of experts from multiple disciplines at Twin Bubble Software Solutions Pvt. Ltd.. This eliminates the redundancy and promotes integration and re-use of data delivering long term benefits by fulfilling the major objective of Data Management.
Data enrichment is a general term that refers to processes used to enhance, refine or otherwise improve raw data. This idea and other similar concepts contribute to making data a valuable asset for almost any modern business or enterprise. It also shows the common imperative of proactively using this data in various ways.
Data cleansing is the process of altering data in a givenstorage resource to make sure that it is accurate and correct. There are manyways to pursue data cleansing in various software and data storage architectures; most of them center on the careful review of data sets and the protocols associated with any particular data storage technology.
Data cleansing is also known as data cleaning or data scrubbing.
A schema mapping is a specification that describes how data structured under one schema (the source schema) is to be transformed into data structured under a different schema (the target schema).
Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually Image Processing system includes treating images as two dimensional signals while applying already set signal processing methods to them.