Solving Data Quality through Data Consolidation

Learn how data consolidation can resolve data quality issues and increase the utility of your data.

Table of Contents

If you struggle with data quality issues, consolidating your data sources is a good first step to resolution. Here are a few ways consolidating data will improve your data quality.

Eliminating Duplicates

When you consolidate data from different sources, you will likely find duplicates. A common challenge we see is parent/child relationships across different data sources. The parent isn’t represented or tagged appropriately leading to multiple parents and inaccurate comparisons. By removing these duplicates, you improve the accuracy and consistency of your data.

Standardizing Data

When you consolidate data, you will likely find variations in how data is formatted or entered. Providing a standardized mapping of attributes that must be tagged to a transaction forces the line-item level data into the aggregated levels needed for meaningful insight. BUCS provides clients with a consolidated mapping tool for customers, accounts, etc. to ensure this consolidated tagging is applied to all transactions, making the data structure consistent. By standardizing data entry, you ensure consistency and make it easier to analyze.

Correcting Errors

When you consolidate data, you will likely find errors in data that require correction. Data quality quickly improves as you increase its usage, making prioritization of historical clean up easier. BUCS also creates automated exception reporting alerting you to errors that need to be addressed in the source data. Recurring errors highlight an opportunity for process review to also improve organizational efficiency. By correcting these errors, you improve the accuracy and value of your data.

Improving Completeness

When you consolidate data, you will likely find missing data fields. A common challenge we see is attribute data related to customers, products, locations and/or vendors missing from application data. We help you connect to multiple data sources to quickly fill in the gaps. By filling in these missing fields, you improve the completeness of your data and its utility.

Conclusion

Overall, consolidating data will help ensure your data is accurate, consistent, and complete, which improves your data quality and increases the reliability of your analyses and decisions.

Having a partner like BUCS with extensive data expertise will ensure you eliminate your data quality issues once and for all. Our client success community will help you develop a strategy to overcome data quality issues and leverage your data as a valuable resource.

Let BUCS help you get started solving your data quality issues through data consolidation.

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