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Methods for Data Cleansing
Using External Data
In the digital age, the data held by companies is vast and increasingly diverse. However, because this data is scattered across different systems and locations, a significant challenge lies in effectively utilizing it. One approach to resolving this situation is Data Federation.
In this article, we explain what Data Federation is, its business benefits, the challenges involved, and the implementation process.
What Is Data Federation?
Data Federation refers to a technology or methodology that enables the use of data stored in different systems or different locations within the same system by providing a virtual environment where data can be accessed under common usage rules, without the need for physical integration. A key feature is the ability to access various data sources while they remain distributed, allowing them to be treated as if they were integrated without the need to centralize the data.
Examples of Data Federation include visualizing information stored in CRMs, ERPs, and data lakes through a unified dashboard while keeping the data in its original location.
Business Benefits of Corporate Data and Data Federation
By leveraging Data Federation, you can achieve the following business benefits:
- Highly Responsive Data Utilization
Data Federation enables the acquisition of the latest information in near real-time. For example, creating a unified viewing environment for sales data across different regions helps in instantly grasping sales trends.
- Reduction of Data Migration Costs
While centralizing data typically requires extensive migration work, Data Federation eliminates the need for such tasks, thereby reducing the costs associated with system resources and time.
- Utilization of Existing Systems
Because Data Federation is a strategy that enables data linkage while utilizing existing storage and applications as they are, it realizes new methods of data utilization while minimizing the impact on existing systems.
- Maintaining Data Governance
Through data federation, data is utilized while remaining in its original location, allowing for integration while maintaining existing security policies. Since there is no need to establish new governance rules, organizations can move to implementation without excessive delays.
- Flexible Data Analysis
Displaying data from different sources in a unified environment promotes interdepartmental collaboration and the discovery of new business insights. For example, analysis combining marketing data with sales data enables the design of more effective campaigns.
Challenges of Data Federation
While data federation offers many benefits, it also presents the following challenges.
- Handling Complex Data Sources
Advanced technology is required to handle data sources stored in different formats and protocols in a unified manner. For instance, there is a high level of difficulty when simultaneously managing SQL databases and unstructured data such as JSON or log data.
- Performance Issues
Because the system requires an environment for real-time access, measures to improve processing speed are necessary when dealing with large volumes of data or insufficient network bandwidth.
- Security and Privacy Risks
When accessing multiple data sources simultaneously, it is necessary to apply security and privacy measures appropriate for each specific data set.
- Lack of Tools and Skills
To succeed with data federation, companies need the right tools and skilled personnel, yet many organizations currently face a shortage of these resources.
Data Federation Process
Data federation is carried out through the following process.
- Identify Data Sources
Identify existing data sources such as CRM, ERP, and data lakes.
- Connection and Access Configuration
Connect data sources using APIs or connectors. Configure access permissions and authentication methods to ensure security.
- Create a Unified Environment
Aggregate necessary data from each data source to create a unified virtual view.
- Data Mapping and Transformation
Standardize data from different formats to ensure it can be utilized in a unified manner.
- Monitor Data Usage
Track usage patterns and monitor performance and errors to drive improvements.
Roles Required to Advance the Data Federation Process
To ensure the success of data federation, the following roles are required.
- Data Architect
Responsible for establishing common rules between data sources and designing connection and unification methods.
- Data Engineer
Executes data connections, transformations, and the implementation of a unified viewing environment.
- Security Expert
Manages the development of authentication environments and security measures related to data access.
- Data Analyst in the Business Department
Extracts insights based on integrated data and proposes methods for business utilization.
The role described above is merely an example; stakeholders collaborate to define data usage requirements and participate in actual operations.
Conclusion
Data federation is an innovative approach that allows companies to utilize distributed data efficiently and flexibly. However, its implementation comes with challenges. Proper technology selection, process design, and the cooperation of a team with specialized skills are essential.
Our customer data integration solution, uSonar, enables the integration of customer information by providing a unique code system. It is possible to streamline the process of establishing common data usage rules, which is necessary when promoting data federation.
Furthermore, by combining unique data provided in conjunction with the uSonar code system with your own internal data, you can identify and correct duplicate or inaccurate information, allowing you to maintain the latest data for your target accounts. By building a unified foundation for customer information, we enable high-precision list generation through the analysis and forecasting of customer trends.
For more details, please feel free to contact us via this page.
