Data management is the process of collecting, using, and keeping data efficiently, cost-effectively, and securely. The primary goal of data management is to help businesses make the most of data while staying within the bounds of rules and regulations so they can make informed decisions and take necessary steps to maximize production and efficiency.
Data is viewed as a corporate asset, which can be used to improve marketing campaigns, make more informed decisions, reduce costs, and optimize business operations. Poor data management can cause big problems for an organization. Inconsistent data sets, incompatible data silos, and data quality issues can limit their ability to perform analytics applications and run business intelligence.
Advantage of Good Data Management
A carefully devised data management strategy can go a long way toward helping companies gain potential competitive benefits over their competitors by enabling better decision making and improving operational effectiveness. Companies with well-managed data can easily spot the latest market trends and take advantage of new business opportunities quickly.
A robust data management strategy can also help businesses avoid data privacy issues, data breaches, and other regulatory compliance issues that could spoil their reputation, land them in hot water, and add unexpected costs. Ultimately, the biggest advantage of having a solid data management strategy is that it provides better business performance.
Types of Data Management:
Data management specialists usually pay attention to domains within the field. These domains or specialties can fall within one or more of the following categories:
Master Data Management – Master Data Management or MDM is the practice of ensuring the company is always using a single version of true information to make informed decisions. Collecting data from different sources and presenting it as a single reliable and constant source requires efficient tools. ‘’Master Data is often referred to as a golden record of info in a data domain, which varies from business to business. It is the core data that is crucial to operations in a particular company or business unit.’’
Data Quality Management – Quality management is accountable for combining and scrutinizing collected data for fundamental issues like inconsistent versions, duplicate records, and more. Data quality management offers a context specific process for improving the quality of data that is used for decision and analysis making. The objective is to offer insights into the fitness of data using different technologies and processes on more complex and increasingly bigger data sets.
Data Security – One of the biggest aspects of data management is security. Although emergent practices include security considerations at all levels of data exchange and application development, security experts are still tasked with preventing unauthorized access, encryption management, protecting against accidental deletion or movement, and other concerns.
Big Data Management – Big Data refers to collecting, analyzing, and employing huge amounts of electronic information to boost operations. This type of data management specializes in integrity, storage, intake of raw data that other teams use to boost security and operations or inform business intelligence.