Data management is the method by which businesses store, manage and secure their data to ensure it remains reliable and usable. It also includes the processes and technologies that support these goals.
The data that is used to run most companies is gathered from various sources, storing it in various systems, and delivered in different formats. It is often difficult for engineers and analysts to find the information they require for their job. This leads to incompatible data silos in which data sets are inconsistent, as well as other issues with data quality which can hinder the use of BI and analytics software and result in inaccurate conclusions.
A process for managing data improves visibility, reliability and security. It can also help teams better understand their customers and deliver the appropriate content at the right time. It’s important to start with clear business goals and then formulate a set of best practices that will develop as the business grows.
A effective process, for example, should support both structured and unstructured data, as well as real-time, batch, and sensor/IoT tasks, and offer pre-defined business rules and accelerators, as well as role-based tools to help analyze and prepare data. It should also be scalable enough to be able to adapt to the workflow of any department. Additionally, it should be able to accommodate different taxonomies as well as allow for the integration of machine learning. It should also be easy to use, with integrated collaborative solutions and governance councils.
