Data Profiling - Data Quality Tools

Put your data under a microscope and see it in a new light

Data profiling can uncover data issues, and be used to monitor data quality over time to ensure data governance processes are working properly to keep bad data out. Melissa's Profiler analyzes data before it’s merged into your warehouse, then helps ensure consistent data quality once it’s there. Use Data Profiler to develop informed strategies on how best to manage and employ your data. Don’t just collect data—make it work for you!

Enhance data governance and data warehousing efforts to drive better business intelligence and analytics throughout the enterprise
Create a metadata repository that aids in building strategic data marts to resolve ambiguities throughout data entities
Enforce business rules on incoming records so you can maintain data standardization, collect data, and format it in a way that is easy to understand and analyze
Showcase ongoing Data Quality improvements to stakeholders, and help convince management of the necessity for Data Quality Budget and Governance initiatives with over 100 types of detailed metadata

Melissa G2 Awards

Always recognized and praised by Melissa Users each quarter on G2.com

Tackle Two Data Quality Predicaments

Data Profiler leverages sophisticated parsing technology and every available general profiling metric to (1) identify data quality issues and (2) monitor improvements over time.

Identification
Identify data quality issues for immediate attention and ensure conformity of source data to specified requirements of pre-set limits.

General Formatting
Data Profiler ensures your input is formatted to your exact specifications. Especially useful for names, emails, postal codes, addresses, and other contact data fields.

Content Analysis

Data Profiler utilizes reference data to determine if your input is consistent with expected data.

Field Analysis

Data Profiler can determine if the input data is consistently fielded using the data contained in the entire record to analyze the context of data.

Monitoring

Good data quality means constantly ensuring what you’ve collected is up-to-date. Profiler allows regexes and error thresholds to be set for full-fledged monitoring, 24/7/365.