Most organizations rely on data, which, in turn, helps them make the right business decisions and thus propel the business. Modern strategies and practices are adopted to capture, store, share, process and retrieve data while minimizing data errors and loss. The platform of data management ensures that the required data is integrated, captured and consolidated accordingly.
In this article, you will get to know the core principles of data management.
What is data management?
It is a specific practice of adopting methodologies, rules, principles and strategies that help in making sure that an organization’s data is utilized optimally.
Following are a few key factors that need to be considered while using data management activity:
Data security: It makes sure that policies are properly implemented for securing data sharing and data access.
Data storage: It makes sure that data is stored properly and accordingly, whether it is private or public cloud, on-premise storage or a hybrid setup.
The following are the principles of data management:
1.Data system design: The following are the key factors that are taken into consideration:
Data system topology: It refers to the interconnectedness of data systems with one another
Data synchronization: This refers to the updation of data across different sources. Different architectural styles are used for implementing data management systems, depending upon the requirements of an organization.
Data inlets and outlets: Sources of data inlets and outlets are identified, right from where it is captured to where it will be transferred to. Multiple applications are used by organizations to gather data such as web forms, accounting software, CRMs, marketing automation, website trackers etc.
2.The importance of creating specific roles and responsibilities for data team: Several data professionals need to be appointed at different levels to handle and streamline the organization’s data efficiently and strategically.
Following are a few key data roles and responsibilities that need to be considered:
Chief Data Officer (CDO): It is an executive-level position. A CDO is responsible for developing strategies that can enable data governance, data quality monitoring and data utilization across the enterprise
Data custodian: The structure of data fields is taken care of by a data custodian, which includes, models and database structures
Data engineer: Data modeling is worked out by data engineer, who is also responsible for building systems that accurately capture, analyze and store data.
Data analyst: Raw data is gathered by a data analyst and then tactically converted into worthwhile insights. The required data is prepared, cleaned and filtered by the data analyst.
3.Data modeling: It means structuring and designing your data assets, their inter-relationships, along with their properties in a logical manner.
The following are the key points that need to be taken into consideration:
The data type and size of each property
The data assets that are stored and managed by an organization (For ex: sales, location and customer product)
The real-world properties that are stored by each asset (For ex: customer data asset has the Customer ID, Email address, phone number, name and residential address)
4.The quality of data: If the dataset contains intolerable defects, then this means that data management practices are not being used optimally. The team’s productivity and efficiency can be affected, if the team thinks that their data is not reliable enough. If data quality errors need to be prevented from entering into the system, then incoming data should be treated as data pipelines, wherein a specific number of operations have been performed.
Conclusion: If you are looking for a productive discussion on the efficacy of data management in resilience and want to know how it can suit your project needs, then just visit online a renowned software testing services company that is ready to serve you profitably.
About the author: I am a technical content writer focused on writing technology specific articles. Software testing is one of the areas in which I’m really interested.
Top comments (0)