Your business relies heavily on data in order to operate, market your products and services, as well as make informed decisions. If the data you have isn’t current, reliable, or relevant to your goals and objectives, then you lose control over your business decisions. Data management is therefore essential for every company, big or small.

In the past, businesses would collect and analyze data using their own software platforms. This could lead to huge data sets that could lead to incompatible and inaccurate findings. Data management is a procedure that connects the information of a company to provide consistent access to, delivery of and governance for business needs. It covers a range of techniques and tools like master data management, data virtualization data catalogs, self-service data preparation and wrangling.

A successful approach to managing data requires striking a balance between security and access to the information your team members require for their work. This requires the implementation of an array of permissions based on roles which allow users to locate the information they require, without compromising the security of your entire inventory. It also requires the use of technology that automatically eliminate mistakes or incorrect entries in data sets, like Data Quality Service Data Quality Service or an automated process for identifying and correcting duplicates.

Your data management process should also be able evolve with your business. For instance, you might want to consider the DataOps approach that combines DevOps and Agile software development methodologies with lean manufacturing principles. This will allow you to create and update pipelines of data faster, and increase collaboration between teams and end-users.