Data management is the practice of collecting, organizing, protecting and storing an organization's data so that it can be analyzed to make business decisions. As organizations create and consume data at an unprecedented rate, data management solutions are becoming essential to making sense of enormous amounts of data. Data management is the practice of collecting, conserving, and using data in a secure, efficient, and cost-effective way. The goal of data management is to help people, organizations and connected things to optimize the use of data within the limits of policies and regulation, so that they can make decisions and take measures that maximize benefits to the organization.
A robust data management strategy is becoming more important than ever, as organizations increasingly rely on intangible assets to create value. Data management is the effective practice of collecting, storing, protecting, delivering and processing data. In business, data is often associated with customers, prospects, employees, offers, competition and finance. When an organization manages data effectively, it obtains information that drives business decisions.
Data management is the process of collecting, storing and using data. It lets you know what data you have, where it is located, who owns it, who can see it and how it is accessed. Data management allows organizations to implement critical systems and applications securely and cost-effectively and participate in strategic decision-making. Data management is a total lifecycle information system that follows data from the moment it is created until it is no longer useful.
But what is data management? And why is it important? What is a data management strategy and what tools can you use to collect, store and analyze your data? More recently, data structures have emerged to help solve the complexity of managing these data systems. Learn more about what better data management can do for you, including the benefits of an autonomous cloud strategy (PDF) and the cloud capabilities of scalable, high-performance databases. While it may be tempting to turn to the IT department to resolve data management issues, it should ideally be a shared responsibility between teams. In the new world of data management, organizations store data in multiple systems, including data warehouses and unstructured data lakes that store any data in any format in a single repository.
Different data management tools and frameworks, such as data structures and data lakes, help eliminate data silos and dependencies of data owners. While data management refers to an entire discipline, master data management has a more specific scope, since it focuses on transactional data. Data management is a necessary measure to ensure that business-critical information is secure, accessible and scalable. As a result, a data management discipline within an organization has become an increasing priority, as this growth has created significant challenges, such as data silos, security risks, and general obstacles to decision-making.
While data processing, data warehousing, data governance, and data security are part of data management, the success of any of these components depends on the company's data architecture or technology suite. Without proper management, you can end up with duplicate records, incorrect information, wasted time and storage space, and a host of other problems typical of a poor organization. Business data platforms typically include software tools for administration, developed by the database provider or by third-party vendors. Data management can help people and companies make better decisions, reduce friction and protect stakeholders.
Your company should take data management very seriously, especially if you're working with customer data. Without a good data management master plan, analysis is virtually impossible at worst and unreliable at best.
