Contact Zone:Introduction

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Contact Zone, is open source data integration software optimized for sophisticated contact data quality. Contact Zone’s uniquely simple approach to data quality incorporates a streamlined graphical user interface enabling data transformations mapped from any source database to any type of data warehouse or target file. Because Contact data is constantly in flux, as people move, new constructions, telephone numbers ported, etc: without processes in place to systematically validate and update the constantly-changing contact information, this data quickly deteriorates. An accurate, single view of these critical information assets can dramatically reduce waste while significantly improving customer communication and business intelligence efforts.

With Contact Zone, users do not need the extensive programming skills or technical understanding of programming languages commonly required to integrate data quality tools. By applying a simple drag-and-drop tool through an intuitive visual interface, Contact Zone users easily target the data to be cleaned. U.S. and Canadian addresses, phone numbers, and email addresses are easily parsed, validated, and corrected for improved segmentation and targeting. Records are updated with U.S. and Canada change-of-address information to help companies stay in touch with moving customers, maximize postal discounts, and reduce undeliverable-as-addressed mail.

Contact Zone Brings the power of Data Quality directly to management staff and database administrators. Contact Zone enables users to get up and running in no time solving business problems by cleansing data at the source. Using the tools in Contact Zone enables power users to conduct data investigations, profile data for accuracy, update and correct data, match data, and measure data quality gaps against set business rules, all without a lick of programming.

Data Quality Tasks

Contact Zone was designed from the ground up to handle many Data Quality related tasks in three different major categories:

Cateogry 1

The first category covers the basics of Contact Data Quality ie: Address Checking, Geocoding, Phone Verification, Name parsing, Email validation and SmartMover (NCOALink) change of address processing. These Data enrichment and cleansing capabilities are available in the first release.

Category 2

The second category of tools for Contact Zone are in the Data Matching area, and specifically the Melissa Data flagship MatchUp component, which organizes data records into identifiable duplicate groups and links/merges related records within or across data sets. This transforms leverages extremely powerful Fuzzy Matching algorithms; (Jaro, n-Gram); (Jaro-Winkler); (n-Gram); and the unique ability to understand common data types found in contact data, such as addresses, nicknames, full names, company names etc: MatchUp enhances the efficiency and effectiveness of your database by giving you the ability to eliminate duplicated customer and prospect records with user specified customizable criteria to realize a single, accurate view of each customer.

Category 3

The third category of Data Quality in the product, available soon, will be the Data Profiler transform. This component is used to analyze individual and multiple columns to determine relationships between columns and tables. The purpose of data profiling tasks is to develop a clearer picture of the content of your data in several ways and examine whether your existing data sources meet the organization’s quality standards. Some of the features of Profiler include Column Profiling – This task identifies problems in your data, such as invalid dates. It reports average, minimum, and maximum statistics for numeric columns. Value Distribution – identifies all values in each selected column and reports normal and outlier values in a column, and Column Pattern Distribution – Identifies invalid strings or irregular expressions in your data. Used altogether Contact Zone covers all the facets of Data Quality as defined by Gartner™, and can be used by organizations large and small to realize the immediate benefits of a Data Quality regimen.

Features and Benefits

Generalized Cleansing

Corrects data values to meet specific business standards, customer business rules, or relationship constraints.

Parsing, Standardization, and Verification

Parses and restructures data into a common format to build more consistent data, such as standardizing addresses to USPS® specifications, or to custom-defined values and patterns specific to a particular business need. Also verifies addresses actually exist.


Adds value to customer data by attaching additional bits of data from other sources including; latitude/longitude coordinates; demographic data; full name parsing; phone number verification; and email validation.


Automates real-time processes to detect when data exceeds pre-set limits so you can immediately recognize and correct issues before the quality of your data declines.

Additional Features

  • Delivers a single view of the customer
  • Access and integrate any data source including large data files
  • Supports data quality and MDM initiatives
  • Access and integrate any data source including big data
  • Lowest cost of ownership
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