6 tools for building a data quality strategy
Determining what type of data quality tools your organization needs depends upon how sophisticated your data quality strategy is. For some companies, a simple data quality approach may be fine, but other organizations may need a very advanced level of data accuracy and data management.
Regardless of your organization’s specific needs, there are a few key universal data quality considerations that are important for any effective approach. Here are six tools that can help with your data quality strategy.
1. Data cleansing: Data cleansing tools are needed when an organization’s data must meet specific domain restrictions, integrity constraints or other business rules. These types of tools provide accurate information for business use. Examples include address verification, email verification, phone validation, etc.