The huge amount of data gathered by businesses requires a well-defined strategy for organizing data, securing and storing it to make it more useful. Anyone who manages their data as an investment can use it to gain insights into customer behavior along with market trends and operational efficiency.
To achieve data management goals, a team with diverse skill sets must work together to collect data and classify it. The data has to be arranged into a useful form. This includes ETL processing that transforms raw data from operational applications such as point-of sale (POS) into a model that is optimized to process data in an analytical manner. It also includes data cleansing in order to eliminate duplicates and maintain integrity of data. Other steps include creating data catalogs that detail the location, security levels https://www.spamreducer.net/the-role-of-technology-in-streamlining-ma-data-management-processes/ and the content of each of your data layers. And then there’s discovery which allows you to search and browse the data tiers for specific data and data sets.
Data management also involves the determination of ownership, access control, and compliance with regulations such as GDPR, CCPA, and others. The ever-changing compliance landscape creates uncertainty over how to handle data and deters companies from investing in a strategy to manage data until they’re certain that they’ll meet the new requirements.
To overcome the barriers of managing data, it is important to establish clear goals for your business. Make sure you are focusing on the most important KPIs when you decide what information to collect, and how to manage it. Then implement the processes needed to achieve those goals.