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US 201403 04062A1 (19) United States (12) Patent Application Publication (10) Pub. No.: US 2014/0304062 A1 Base et al. (54) (43) Pub. Date: ENTERPRISE DATA REMATCHING Publication Class?cation (71)

How to fill out enterprise data re-matching

How to fill out enterprise data re-matching:

1. Identify the purpose of the enterprise data re-matching. Determine why you need to re-match the data and what specific objectives or outcomes you hope to achieve.
2. Gather the relevant data sources. Identify all the datasets and databases that need to be re-matched and ensure you have access to them.
3. Clean and prepare the data. Before re-matching, it is crucial to clean the data and ensure its quality. Remove duplicates, correct errors, and standardize formats if necessary.
4. Determine the matching criteria. Define the rules or algorithms that will be used to match the data. This can include matching based on identifiers, attributes, or specific rules.
5. Perform the data re-matching process. Use the defined matching criteria to compare and link the data records. This may involve using advanced algorithms or matching software.
6. Validate the re-matched data. Review the results of the re-matching process and validate the accuracy of the matched records. Identify any potential errors or discrepancies.
7. Integrate the re-matched data. Once the data is validated, integrate the re-matched records back into the appropriate systems or databases.
8. Monitor and maintain the re-matched data. Continuously monitor the re-matched data to ensure its accuracy and update it as needed.

Who needs enterprise data re-matching:

1. Businesses with growing customer databases. As a business expands and accumulates more customer data, there is a higher likelihood of duplicate or inconsistent records. Enterprise data re-matching can help consolidate and unify customer information.
2. E-commerce companies. Given the large volume of transactions and customer data involved, e-commerce companies often face challenges with inaccurate or duplicate data. Re-matching data can enhance their data accuracy and improve various areas of their operations.
3. Healthcare organizations. In the healthcare industry, accurate and up-to-date patient information is critical. Enterprise data re-matching can help healthcare organizations ensure that they have a complete and accurate view of each patient's medical records.
4. Financial institutions. Banks and financial institutions handle a vast amount of customer data, including personal and transactional information. Re-matching data can help them identify and resolve data discrepancies, improve fraud detection, and enhance customer service.
5. Government agencies. Government organizations often manage large volumes of data across various departments or systems. Re-matching data can help them consolidate information, improve data quality for decision-making, and streamline administrative processes.

For pdfFiller’s FAQs

What is enterprise data re-matching?

Enterprise data re-matching is the process of comparing and updating existing data records within an organization's database to ensure accuracy and consistency.

Who is required to file enterprise data re-matching?

All businesses or organizations that collect and store large amounts of data are required to file enterprise data re-matching.

How to fill out enterprise data re-matching?

Enterprise data re-matching can be filled out by using specialized software or tools that automatically compare and update data records.

What is the purpose of enterprise data re-matching?

The purpose of enterprise data re-matching is to maintain data integrity, improve data quality, and ensure that accurate information is available for decision-making.

What information must be reported on enterprise data re-matching?

Enterprise data re-matching must report information such as updated data records, any changes made, and the date of the re-matching process.

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