Data management is a method to how companies collect, store and secure their data to ensure that it remains effective and reliable. It also encompasses the technology and processes that aid in achieving these goals.

The information that runs the majority of companies comes from a variety of sources, and is stored in numerous systems and places and is usually delivered in a variety of formats. It can be difficult for engineers and analysts to find the information they need for their work. This leads to discordant data silos and look what i found incompatible data sets, in addition to other data quality problems that can limit the usefulness and accuracy of BI and Analytics applications.

A process for managing data will improve the visibility and security as well as reliability, enabling teams to better comprehend their customers and provide the appropriate content at the right time. It’s important to start with clear business goals and then develop a set of best practices that will expand as the business expands.

A effective process, for example, should support both structured and unstructured data as well as real-time, batch, and sensor/IoT workloads, while offering pre-defined business rules and accelerators, plus role-based tools that help analyze and prepare data. It should be scalable to accommodate the workflow of any department. It must also be flexible enough to allow integration of machine learning and accommodate different taxonomies. Furthermore, it should be accessible via built-in collaborative solutions and governance councils for consistency.