What is Data Redundancy?
Data redundancy occurs when the same piece of data is held within a database or data storage technology. Data can reoccur in two different fields within a single database, or two different spots in multiple software platforms or environments. Data redundancy can arise by accident, but can also be done deliberately for backup and recovery purposes.
Accidental data redundancy can happen when data ends up being duplicated due to inefficient coding or process complexity, whereas purposeful data redundancy can often safeguard data and promote consistency.
It is fine for data to be stored in multiple places; in order to avoid problems, it’s important to have a central, master field or space for this data, so that there is a way to update all of the places where data is redundant through a single access point. Otherwise, this type of data redundancy can lead to data inconsistency, where one update does not automatically update another field. Pieces of data that are supposed to be identical end up having different values, which can lead to problems with processing.
How MDM Can Reduce Data Redundancy
Data redundancy is a common issue in many organizations. Most large enterprises have a heterogeneous application portfolio, with fragments of often inaccurate, incomplete, and inconsistent data residing in various application silos. Data redundancy often occurs with companies wanting a consistent view of their customer base; they can struggle to reconcile data across numerous operational systems.
What is Data Redundancy? now.
For example, a customer might be known as Ms. Smith in one system and Theresa Smith in another. These issues cause intelligent decision making to be difficult— but solving these problems lies in how shared data is handled.
Master Data Management (MDM) is a comprehensive method of enabling an enterprise to link all of its critical data to one "master file" that provides a common point of interest. Examples of master data include customer, product, asset, location, employee, organizational unit.
MDM has emerged as a means to more efficiently manage shared data, eliminate data redundancy, and create the elusive "single version of the truth." MDM is able to offer both data consistency and agility, therefore providing a major competitive advantage and return on investment (ROI).
As businesses strive to dramatically reduce costs, meet compliance reporting mandates, deliver increased sales, and provide superior service to customers and suppliers, analysts have declared MDM as a solution which will significantly contribute to these business priorities.
Master Data Management comprises a set of processes and tools that consistently defines and manages the non transactional data entities of an organization. Its objective is to provide processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information.
What is Data Redundancy? now.
How Talend’s MDM Solution Solves Data Redundancy Issues
Talend MDM is a model-driven, non intrusive solution easily adaptable to specific business needs and quick to implement. It has been specifically developed to address the challenges of creating and managing master data for all types of organizations where data is hosted under various formats in various systems and can be extremely volatile.
It provides a complete set of features for mastering, governing and integrating data throughout the enterprise. Talend MDM groups all master data of the company in a central hub. This standardized repository provides, via the use of data models, the prerequisites against which data and updates are validated.
Talend Studio, a key part of Talend’s MDM solution, is particularly well suited to issues arising from data redundancy. Talend Studio provides the processing layers that ensure the right people have the right tools to centrally model and manipulate master data. This key capability comprises the relevant features involved in master data governance and stewardship.
Data governance is the process of defining the rules that master data has to follow. Data stewardship is the process of making sure that the data follows those rules. This means that it is necessary to have both a governance function, to demonstrate that the right controls are in place, and a stewardship function, to ensure that the controls are enforced.
Inside Talend Studio you will find:
- Data profiling and quality features, available from the Profiling perspective, that enable the profiling and cleansing of the source data before loading it into the MDM Hub, to help guarantee high standards of master data quality in your company. From the Profiling perspective, users can profile and clean data from various sources before loading it into the MDM Hub.
- Master data management features, available from the MDM perspective, that enable you to build data models employing the necessary business and data rules to create one single master copy of the data which will be propagated back to the source and target systems.
- Data resolution features, provided within Talend MDM Web User Interface through Talend Data Stewardship Console, to deal with records that arrive following a match operation from different data sources and where a decision needs to be taken to come up with the golden master data record.
As the amount, sources, and variety of data grows, data redundancy is also growing to become a headache for data-driven enterprises. Master Data Management solutions can go a long way to mitigate data redundancy problems.
Try Talend’s open source product for MDM today.