Data management is a procedure which involves the creation and implementation of policies, procedures and processes to handle data throughout its entire life cycle. It makes sure that data is available and useful, facilitates the compliance of regulators and makes informed decisions and ultimately gives businesses with an edge in the market.
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 must be consolidated, and then delivered to business intelligence (BI) and analytics systems, enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors, machine learning and Artificial Intelligence generative (AI) tools for advanced insights.
Without a well-defined data management strategy, companies can end up with uncompatible data silos and unbalanced data sets that hinder the ability to run analytics and business intelligence applications. Inadequate data management can affect the confidence of employees and customers.
To meet these challenges businesses must create an effective data-management plan (DMP) which includes the people and processes required to manage all kinds of data. For example, a DMP can help researchers identify the naming conventions for files they should employ to structure data sets to ensure long-term storage as well as easy access. It can also contain data workflows that define the steps that must be followed for cleansing, validating and integrating raw data sets and refined data sets to make them suitable for analysis.
A DMP can be used by organizations that collect consumer data to ensure compliance with privacy laws at the global and state level, for example, the General Data Protection Regulation of https://taeglichedata.de/how-to-set-up-a-relevant-and-useful-deal-room/ the European Union or California’s Consumer Privacy Act. It can be used to guide the development and implementation of policies and procedures to address security threats to data.
