Data management is a method that involves creating and enforcing procedures, policies and procedures to manage data throughout its entire life cycle. It ensures that data is reliable and easily accessible, facilitates compliance with regulations, and allows for informed decisions.
The importance of effective data management has grown significantly as organizations automate their business processes, leverage software-as-a-service (SaaS) applications and deploy data warehouses, among other initiatives. This results in a plethora of data that needs to be consolidated and delivered to business intelligence (BI) and analytics systems, enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors, machine learning and artificial intelligence (AI) tools to provide advanced insights.
Without a clearly defined data management strategy, companies could end up with uncompatible data silos and inconsistent data sets that hinder the ability to run business intelligence and analytics applications. Data management issues can cause distrust between customers and employees.
To meet these challenges companies need to develop a plan for managing data (DMP), which includes the people and processes required to manage all types data. For example, a DMP can help researchers identify the naming conventions for files they should apply to organize data sets for long-term storage and access. It may also include data workflows which define https://taeglichedata.de/master-data-management-the-first-steps-in-data-consolidation/ the steps to follow to cleanse, validate, and integrating raw data sets as well as refined data sets to allow them to be suitable for analysis.
For companies that gather consumer information For companies that collect consumer information, a DMP can help ensure compliance with privacy laws around the world like the European Union’s General Data Protection Regulation or state-level regulations like California’s Consumer Privacy Act. It can also guide the formulation of policies and procedures to deal with security threats to data and audits.