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Data Consolidation

What is Data Consolidation

Data consolidation is the process of combining data from multiple sources or systems into a single, unified view. This process is often used to integrate data from different departments or business units within an organization or to combine data from external sources with internal data.

Data consolidation is typically performed to improve data quality, create a more comprehensive view of an organization's data, and facilitate data analysis and decision-making. It can be useful in a variety of applications, including financial reporting, market research, and customer relationship management.

There are several approaches to data consolidation, including manual, automated, and hybrid methods. Manual data consolidation involves manually combining data from different sources using tools such as spreadsheet software or database management systems. Automated data consolidation involves using software or tools to automatically extract, transform, and load data from different sources into a single repository. Hybrid approaches combine elements of both manual and automated data consolidation.

Data consolidation can be a complex and time-consuming process, as it requires careful planning and management to ensure that the data being consolidated is accurate, consistent, and complete. It is also important to consider the security and privacy implications of consolidating data from multiple sources.


See Also

  1. Data Integration
  2. Extract, Transform, Load (ETL)
  3. Data Warehouse
  4. Data Aggregation
  5. Data Migration
  6. Master Data Management (MDM)
  7. Data Quality
  8. Database Management System (DBMS)
  9. Data Governance
  10. Business Intelligence



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