Data management is the process of establishing and enforcing rules, processes and procedures for handling data throughout its entire lifecycle. It makes sure that data is available and useful, facilitates regulatory compliance and informed decision-making 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 needs to be consolidated, and then delivered to business intelligence (BI) and analytics systems and enterprise resource planning (ERP) platforms, Internet of Things (IoT) sensors and machine learning and artificial intelligence (AI) tools for advanced insights.
Without a clearly defined data management plan, businesses can end up with incompatible data silos and unbalanced data sets which make it difficult to run business intelligence and analytics applications. Inadequate data management can cause distrust between customers and employees.
To meet these challenges it is crucial that companies develop a data management plan (DMP) that includes the people and https://taeglichedata.de/generated-post/ processes needed to manage all types of data. For example the DMP can assist researchers in determining the naming conventions that they should follow to organize data sets to ensure long-term storage and for easy access. It could also include data workflows that define the steps to be taken to cleanse, validate, and integrating raw data sets and refined data sets to make them suitable for analysis.
For companies that gather consumer information, a DMP can assist in ensuring compliance with global privacy laws such as the European Union’s General Data Protection Regulation or state-level regulations such as California’s Consumer Privacy Act. It can also guide the development of policies and procedures for dealing with data security risks and audits.
