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Jan 82 min read

How Can a Data Quality Assessment Identify and Resolve CRM Data Quality Issues?

Introduction

ActivePrime’s Data Quality Assessment (DQA) provides your organization with a holistic insight into the current state of Salesforce data and highlights areas that require attention with solutions to enhance data quality to support critical initiatives like AI. No amount of AI power can overcome poor data quality.



How does a DQA Identify My Organization’s Data Issues?

A DQA is a read-only assessment that gives you visibility into the current state of your data.  It leverages an AI engine that has been specifically trained to understand what data is beyond just text or numbers. The model understands what constitutes a Name, Account Name, Title, Addresses, Phone, Email and other Semantic Types to provide relevant insights across multiple dimensions. 


  1. Comprehensive Data Quality Checks Across 7 Key Dimensions

ActivePrime helps your organization identify duplicates and 6 other key data issue dimensions that are often overlooked. These additional dimensions are:

  1. Formatting Issues: Ensures data consistency by flagging format inconsistencies.

  2. Junk Data: Removes irrelevant or non-informative entries that could clutter Salesforce.

  3. Missing Data: Identifies incomplete records and gaps in essential information.

  4. Misplaced Data: Detects values in incorrect fields (e.g., emails in phone fields).

  5. Incorrect Data: Flags inaccuracies to ensure data reliability and minimize errors.

  6. Damaged Data: Identifies and addresses corrupted data, preventing potential system performance issues.


  1. AI-Driven Duplicate Detection

Smart Fuzzy Matching: ActivePrime utilizes advanced AI techniques to detect duplicate records that traditional tools might miss. This includes recognizing variations like "Acme INC" and "Acme LTD" as duplicates by analyzing context and specific field importance. The AI-driven Smart Fuzzy Matching provides a more accurate and comprehensive approach to duplicate detection that considers Semantic Types to go beyond matching values based on similar strings.


  1. AI-Driven Contextual Understanding on Other Key Data Issue Dimensions

ActivePrime’s AI understands the context and field-specific patterns for the 6 data issue dimensions mentioned in point 1. This reduces the potential for false positives and enhances accuracy. For example, the AI understands that a valid email address in the Phone Number field is not Junk Data. Instead, the AI automatically identifies the email address as Misplaced Data and recommends the appropriate correction.


  1. Actionable Insights

After the assessment, your organization receives a readout and a comprehensive 

report highlighting the identified data issues, insights into data patterns, and prioritized recommendations. This helps your organization to take immediate, data-driven actions to improve Salesforce data quality.


Conclusion

By leveraging ActivePrime’s complimentary DQA, your organization can take the first step toward achieving high-quality, reliable data in Salesforce that supports AI and other critical business initiatives. Your organization can reveal specific data quality challenges in Salesforce with actionable insights and strategies to enhance the quality of the data.


Click here to request your Data Quality Assessment and take your first step toward achieving high-quality data today.

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