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Record Matching Made Easy with MatchUp Web Service

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MatchUp®, Melissa's solution to identify and eliminate duplicate records, is now available as a web service for batch processes, fulfilling one of most frequent requests from our customers - accurate database matching without maintaining and linking to libraries, or shelling out to the necessary locally-hosted data files.


Now you can integrate MatchUp into any aspect of your network that can communicate with our secure servers using common protocols like XML, JSON, REST or SOAP.

 

Select a predefined matching strategy, map the table input columns necessary to identify matches to the respective request elements, and submit the records for processing. Duplicate rows can be identified by a combination of NAME, ADDRESS, COMPANY, PHONE and/or EMAIL.

 

Our select list of matching strategies removes the complexity of configuring rules, while still applying our fast and versatile fuzzy matching algorithms and extensive datatype-specific knowledge base, ensuring the tough-to-identify duplicates will be flagged by MatchUp. 


The output response returned by the service can be used to update a database or create a unique marketing list by evaluating each record's result codes, group identifier and group count, and using the record's unique identifier to link back the original database record.

 

Since Melissa's servers do the processing, there are no key files - the temporary sorting files - to manage, freeing up valuable hardware resources on your local server.

 

Customers can access the MatchUp Web Service license by obtaining a valid license from our sales team and selecting the endpoint compatible to your development platform and necessary request structures here.

Full Spectrum Data Quality Toolkit Enhances Customer Data in Real-Time; 

Includes Advance Look at New Generalized Cleansing Component for All Types of Data


Rancho Santa Margarita, CALIF - October 19, 2016 - Melissa Data, a leading provider of global contact data quality solutions, today announced active data quality tools and services for SQL Server Integration Services (SSIS). Database administrators (DBAs) and SSIS developers can cleanse, standardize, and enrich customer data in real-time, capitalizing on tools that access multi-sourced, constantly updated reference datasets. These full spectrum data quality add-ons assure only accurate, enhanced data enters the system, with capabilities including global address, name, phone and email verification, ID verification, move updating, and firmographic enrichment.


Melissa Data's active data quality tools are also expanding to include all data types; SSIS users can request here a free trial of the company's new Generalized Cleansing Component, a breakthrough in integrating different types of cleansing rules scripted into a single tool. Features such as search and replace, or a range of cleansing, standardizing, and reformatting capabilities are included, as well as the ability to create customized triggering rules to standardize any type of data.


"Active data quality recognizes that customer data is not static, operating in real-time to assure accurate, actionable customer data," said Bud Walker, vice president of enterprise sales and strategy, Melissa Data. "This approach relies on smart, sharp tools to ensure data quality all along the data stream, creating business value that will extend to other data types with our new Generalized Cleansing Component."


In addition to SSIS, Melissa Data works closely with the range of Microsoft technologies including .NET and Excel, providing flexible data quality tools to support varied enterprise requirements. Click here to download a free trial of Melissa Data's comprehensive data quality toolkit available for integration with SSIS. For a demonstration, visit Melissa Data at PASS Summit in Seattle, Booth #609, October 24-28; or call 1-800-MELISSA.

The Ultimate Guide to SQL Server Data Quality

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We can all pretty much agree that there are pros and cons to integrating data quality from shared procedures. SQL Server technology offers various options when it comes to integrating third party solutions. Knowing the right route to take can be determined by preference in architecture. Here are a couple of the most commonly used ways to integrate Melissa Data's flagship Data Quality Solutions within SQL Server:


1. Transact-SQL OLE Automation Objects

 

Melissa Data supports the integration of OLE Automation Objects for the sake of legacy versions of SQL Server while also enabling the registering of COM Object library interfaces with sp_OACreate. Due to the in-process constraints this method contains, it is one we least advocate for integration.

 

2. Extended Stored Procedures

 

This is the most common ways users call the Melissa Data API's. It allows for accessing third party DLLs and offers a quick and easy way to connect to SQL Databases to iterate record through Data Cleansing regimens. Wrapper functions are automatically generate allowing for direct access to APIs.

 

3. Common Language Runtime (CLR) Integration

 

This is the least common integration method. However, it is not the least effective. This integration allows for calling .NET Code from SQL Server to perform transformations for your data. It results in performing tasks that may have been previously impossible due to limitations of queries. Melissa Data's APIs can be called through a .NET project in your CRL Project as opposed to calling it through an Extended Stored Procedure. This offers a more stable platform when working with DLLs and we highly recommend it.

 

4. SQL Server Integration Services

 

Another common implementation method is SSIS-an ETL/Data Integration Platform Bundles with SQL Server. We provide custom GUI-based components for SSIS that are accessible through the Data Flow Task. Our integration with SSIS is seamless and easy to use as it makes an interface and does not require any type of coding. We support both 2008 and 2012 versions of SQL Server.

 

5. SQL Server Data Quality Services (DQS)

 

DQS is a data quality solution developed by Microsoft and offered in the Microsoft Azure Marketplace. It offers third party reference services which integrate with Melissa Data's flagship suite of Data Cleansing Solutions. Melissa Data's solutions in the Microsoft Azure Marketplace can be consumed within DQS Platform.

For more information, or to learn about SQL Server data quality, visit our website!


By Natalia Crawford


Flagship SSIS Developer Suite Now Enables Data Assessment and Continuous Monitoring Over Time; Webinar Adds Detail for SSIS Experts


Rancho Santa Margarita, CALIF - March 17, 2015 - Melissa Data, a leading provider of contact data quality and address management solutions, today announced its new Profiler tool added to the company's flagship developer suite, Data Quality Components for SQL Server Integration Services (SSIS). Profiler completes the data quality circle by enabling users to analyze data records before they enter the data warehouse and continuously monitor level of data quality over time. Developers and database administrators (DBAs) benefit by identifying data quality issues for immediate attention, and by monitoring ongoing conformance to established data governance and business rules.

Register here to attend a Live Product Demo on Wednesday, March 18 from 11:00 am to 11:30 am PDT. This session will explore the ways you can use Profiler to identify problems in your data.

"Profiler is a smart, sharp tool that readily integrates into established business processes to improve overall and ongoing data quality. Users can discover database weaknesses such as duplicates or badly fielded data - and manage these issues before records enter the master data system," said Bud Walker, director of data quality solutions, Melissa Data. "Profiler also enforces established data governance and business rules on incoming records at point-of-entry, essential for systems that support multiple methods of access. Continuous data monitoring means the process comes full circle, and data standardization is maintained even after records are merged into the data warehouse."

Profiler leverages sophisticated parsing technology to identify, extract, and understand data, and offers users three levels of data analysis. General formatting determines if data such as names, emails and postal codes are input as expected; content analysis applies reference data to determine consistency of expected content and field analysis determines the presence of duplicates.

Profiler brings data quality analysis to data contained in individual columns and incorporates every available general profiling count on the market today; sophisticated matching capabilities output both fuzzy and exact match counts. Regular expressions (regexes) and error thresholds can be customized for full-fledged monitoring. In addition to being available as a tool within Melissa Data's Data Quality Components for SSIS, Profiler is also available as an API that can be integrated into custom applications or OEM solutions.

Request a free trial of Data Quality Components for SSIS or the Profiler API.
Call 1-800-MELISSA (635-4772) for more information.

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Make more in formed decisions about sales clustering, risk exposure, tax jurisdictions, market segmentation, logistics and more by geocoding addresses. Geocoding appends latitude and longitude coordinates to the rooftop of an address - delivering the most accurate location possible. Find out how to start geocoding addresses to the rooftop in this quick 5-minute tutorial now! The video highlights geocoding in our data quality software Contact Zone, but we also offer geocoding solutions in SSIS, Listware, in the Cloud, and in our API tools.

Watch our video now!

In three easy steps, Melissa Data's product specialist Matthew Bayne demonstrates how Personator for SQL Server Integration Services (SSIS) cleans, verifies, standardizes, and appends missing information such as email addresses and phone numbers - to complete your contact records, help reduce fraud, and improve your marketing efforts.

Watch our video now!



Powerful Features Support Developers with Enriched, De-Duplicated Customer Records; Combats Exponential Increase in Costly Data Decay, Highlighted in Company Magazine


Rancho Santa Margarita, CALIF. - October 29, 2014 - Melissa Data, a leading provider of global contact data quality and data enrichment solutions, today announced significant enhancements to its flagship Data Quality Components for SQL Server Integration Services (SSIS), including the addition of three new services: global email, global phone verification, and U.S. property data enrichment. Data Quality Components for SSIS is a suite of custom data cleansing transformation components for Microsoft SSIS, used to standardize, verify, correct, consolidate and update contact data. With these new features, developers and DBAs are positioned to verify, enrich and retain all the best pieces of global customer data, using a single comprehensive and proven data quality tool.

New to the suite of tools is global email verification, which includes real-time email mailbox verification to eliminate up to 95 percent of invalid emails, so emails get delivered and don't bounce. Global phone numbers from over 230 countries can be verified and appended with geographic information, such as latitude and longitude coordinates, administrative area and predominant language spoken in that region. In addition, global phone features include the ability to return the digits necessary to dial out of your country and into the country of the phone number that was input. For users seeking to enrich U.S. address data, the property feature will provide up-to-date property and mortgage information on more than 140 million properties to improve overall customer intelligence.

"Contact data is always in flux, in fact, half of the customer records held in the average database are invalid or out-of-date in just 45 months - what we call the half-life of data," said Bud Walker, director of data quality solutions, Melissa Data. "Particularly as data becomes more global and increasingly includes email as a critical path of contact, database design must incorporate flexible, scalable tools that rely on a comprehensive approach to managing constant changes in customer data."

Melissa Data's research into the half-life of data, including the operation and long-term costs associated with undeliverable shipments, low customer retention and unsuccessful CRM initiatives, along with other SQL-based data quality challenges are featured in the current issue of Melissa Data Magazine, the company's quarterly resource for DBAs and data quality developers.

Melissa Data Magazine will be available at PASS Summit 2014, Booth #407, starting November 4 in Seattle, Washington. Click here to download the SQL Server edition of Melissa Data Magazine, or call 1-800-MELISSA (635-4772) for more information.

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New Company Magazine Features Data Quality Insights on Merging Duplicate Patient Records into a Golden Record, also Tips on Improving Healthcare Data Warehousing



Rancho Santa Margarita, CALIF. - September 9, 2014 - Melissa Data, a leading provider of global contact data quality and data enrichment solutions, today announced matching and de-duping functionality that solves duplicate records for healthcare database administrators (DBAs). Using tools based on proprietary logic from Melissa Data, healthcare DBAs can consolidate duplicate customer records objectively, unlike any other data quality solution. This and other healthcare data quality challenges are featured in Melissa Data Magazine, the company's new quarterly resource for DBAs and data quality developers.

Healthcare data is characterized by a steady stream of patient records and evolving contact points, warranting a smart, consistent method to determine the best contact information. Melissa Data Magazine highlights a new way to merge duplicate records, based on a unique data quality score that retains the best pieces of data from all of the various records.

"It's essential that healthcare data managers acknowledge data quality challenges up front, implementing processes to cleanse and maintain the trustworthiness of the information that goes into their master data systems," said Bud Walker, director of data quality solutions, Melissa Data. "Our new publication outlines how to ensure this high level of data precision, creating an accurate, single view of the patient. This is known as the Golden Record and is of critical value in healthcare settings - reducing costs, streamlining business operations and improving patient care."

Highlighting industry-specific data quality tools and solutions, Melissa Data Magazine will help DBAs and health information managers adapt to evolving challenges particularly as data becomes more global in nature. Future published issues will feature technologies such as SQL Server development tools, and markets such as retail, ecommerce, government and real estate.

Melissa Data Magazine will be available at the American Health Information Management Association (AHIMA) conference, Booth #723, starting September 27 in San Diego, Calif. Click here to download the healthcare issue of Melissa Data Magazine, or call 1-800-MELISSA (635-4772) for more information.

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A 6-Minute MatchUp for SQL Server Tutorial

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In this short demo, learn how to eliminate duplicates and merge multiple records into a single, accurate view of your customer - also known as the Golden Record - through a process known as survivorship using Melissa Data's advanced matching tool, MatchUp for SQL Server.

Watch our video to learn more!


Data Quality Tool Consolidates Duplicates into Single Golden Record of Customer Data; Uniquely Determines Most Accurate Information Based on Objective Data Quality Score


Rancho Santa Margarita, CALIF- April 23, 2014 - Melissa Data, a leading provider of contact data quality and integration solutions, today announced new matching and de-duplication functionality in its MatchUp Component for SQL Server Integration Services (SSIS), uniquely solving the business challenge of duplicate customer data. Based on proprietary logic from Melissa Data, MatchUp determines the best pieces of data to retain versus what to discard - consolidating duplicate records objectively, unlike any other data quality solution. By assessing the quality of individual data fields, MatchUp enables a smart, consistent method for database administrators (DBAs) to determine the best customer contact information in every field.

"The average database contains 8 to 10 percent duplicate records, creating a significant and costly business problem in serving, understanding and communicating with customers effectively. The ideal is a single, accurate view of the customer - known as a golden record - yet this remains one of the biggest challenges in data quality based on methodologies that don't adequately evaluate the content of each data field. As a result, DBAs either overlook duplicates or consistently struggle with determining what information survives in the database and why," said Bud Walker, director of data quality solutions, at Melissa Data. "By using intelligent rules based on the actual quality of the data, DBAs are much better positioned to retain all the best pieces of information from two or more duplicate records into a single, golden record that provides valuable insight into user behavior and helps boost overall sales and marketing performance."

MatchUp works in sharp contrast to matching and de-duplication methods that rely solely on subjective principles, such as whether the record is the most recent, most complete or most frequent. Instead, selection criteria for determining a golden record is based on a relevant data quality score, derived from the validity of customer data such as addresses, phone numbers, emails and names. Once the golden record is identified intelligently, MatchUp further references the data quality score during survivorship processes to support creation of an even better golden record; duplicate entries are then collapsed into a single customer record while retaining any additional information that may also be accurate and applicable.

Utilizing deep domain knowledge of names and addresses, survivorship operations with MatchUp can granularly identify matches between names and nicknames, street/alias addresses, companies, cities, states, postal codes, phones, emails, and other contact data components.

Melissa Data will be demonstrating its MatchUp Component for SSIS at booth #46 during Enterprise Data World, April 27-May 1, 2014 at The Renaissance Hotel in Austin, TX. To download a free trial of Melissa Data's MatchUp Component for SSIS, click here or call 1-800-MELISSA (635-4772).

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