5 Risks of Building a Data Management Application
Posted: Tue Jan 21, 2025 5:06 am
When deciding whether to buy or build your own data management platform or application, it's important to be aware of these 5 build risks.
Any attempt to build a data management application should begin with an assessment of the enterprise data management situation in the organization . It is necessary to understand the efforts currently being made regarding data management, metadata management, data architecture, data quality management, data integration practices , etc.
From this assessment, the organization can develop an approach to data management that enables improvements where necessary in each area and will enable it to develop an appropriate enterprise data management framework, including the evaluation and selection of technology and the development of strategic objectives.
Importance of data in digital transformation
Data processing stages to implement a data management application
Once the assessment is complete, these are the basic fantuan database that should be applied to the data to implement a data management application:
Discovery – Document and model essential business data and processes to use common data, identify all data sources, and define metadata.
Analysis . Identify data sources for the chosen subject area, evaluate data flow and transformation rules, refine metadata definitions, and define data quality requirements .
Construction . Creation of the data management application database according to the architecture that has been created.
Implementation . Populating the database with data from the first subject area and associated metadata, defining and implementing access rights, designing change management processes and assessing data quality levels.
Maintenance . Implement change management internally for the first iteration, while planning and deploying the next, and then continue moving forward in similar stages until the data management application is finished.
Risks of building a data management platform
The risks of building a data management platform are related to the potential delays that may be involved in the construction of the platform, delays that inevitably entail financial losses.
These delays can occur for several reasons, such as:
Lack of corporate support for the implementation of technology.
That there is clear resistance to change.
The adoption of new technologies .
The existence of poor specification and management of suppliers.
The company's own internal inertia .
All of them point to a clear delay, which entails more costs and in turn less income for the company.
Another risk apart from the delay would be the possibility that what was built would not work once the work is finished , which again translates into extra time and cost but with an even higher rate of severity.
Furthermore, it must be taken into account that industrialized applications usually already have the best practices on the market , which is not the case with custom development, and in this sense not adopting the Best Practices for this type of technology would imply being less efficient .
Any attempt to build a data management application should begin with an assessment of the enterprise data management situation in the organization . It is necessary to understand the efforts currently being made regarding data management, metadata management, data architecture, data quality management, data integration practices , etc.
From this assessment, the organization can develop an approach to data management that enables improvements where necessary in each area and will enable it to develop an appropriate enterprise data management framework, including the evaluation and selection of technology and the development of strategic objectives.
Importance of data in digital transformation
Data processing stages to implement a data management application
Once the assessment is complete, these are the basic fantuan database that should be applied to the data to implement a data management application:
Discovery – Document and model essential business data and processes to use common data, identify all data sources, and define metadata.
Analysis . Identify data sources for the chosen subject area, evaluate data flow and transformation rules, refine metadata definitions, and define data quality requirements .
Construction . Creation of the data management application database according to the architecture that has been created.
Implementation . Populating the database with data from the first subject area and associated metadata, defining and implementing access rights, designing change management processes and assessing data quality levels.
Maintenance . Implement change management internally for the first iteration, while planning and deploying the next, and then continue moving forward in similar stages until the data management application is finished.
Risks of building a data management platform
The risks of building a data management platform are related to the potential delays that may be involved in the construction of the platform, delays that inevitably entail financial losses.
These delays can occur for several reasons, such as:
Lack of corporate support for the implementation of technology.
That there is clear resistance to change.
The adoption of new technologies .
The existence of poor specification and management of suppliers.
The company's own internal inertia .
All of them point to a clear delay, which entails more costs and in turn less income for the company.
Another risk apart from the delay would be the possibility that what was built would not work once the work is finished , which again translates into extra time and cost but with an even higher rate of severity.
Furthermore, it must be taken into account that industrialized applications usually already have the best practices on the market , which is not the case with custom development, and in this sense not adopting the Best Practices for this type of technology would imply being less efficient .