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Data Quality Components for SQL Server®

Full Spectrum Data Quality to Manage the Lifecycle of Your Data

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Data Quality Components for SQL Server

Data Quality Components for SQL Server Integration Services (SSIS) enable you to clean, complete, and consolidate your People Data, so you know it’s trustworthy and actionable.

Our data quality components offer a full spectrum of solutions to profile, cleanse, verify, match, merge, purge, parse, standardize, and enrich with geographic, demographic, and firmographic insights.

  • Profile and analyze data from any source for discovery
  • Validate, correct and standardize all data types
  • Transform and reconcile all data types for improved integration
  • Deliver the right data, at the right time, in the right format across the enterprise
Profile your data to gain valuable insight with Melissa's Profiling Component for SSIS.

Profiling Component

Poor data quality equals poor business. The first step in improving data quality is to profile your data to gain valuable insight into the accessiblilty and usability of your data. The Data Profiling component does just that – it generates simple to advanced profiling information – including basic data statistics (mean, median, frequency, variation, etc.) and details (structure, content, classifications, etc.). Armed with this information you can identify weak points in your data collection processes and work to optimize data quality over time with the Profiling Component's monitoring capabilities.

Generalized Cleansing Component

The Generalized Cleansing Component empowers you to build data cleansing scripts for data suffering from a wide range of errors and inconsistencies. The component combines six operations that allow you to cleanse data and save operations (simple or complex) for future projects. The component is highly customizable so you can use programmatic expressions and regular expressions to trigger operations – giving you the ability to self-validate non-contact data to your own specifications.

Cleansing Operations Available:

  • Casing – change the casing of data from capital to lowercase, etc.
  • Punctuation – add or remove punctuation
  • Abbreviation – expand or contract abbreviations, for example: CA to California
  • Search and Replace – replace portions of a string
  • Expressions – create programmatic expressions to make sense of data values
  • Regex – use regular expressions to extract, validate, etc.
Empower your data and build data cleansing scripts for data suffering from a wide range of errors and consistencies with Melissa's Generalized Cleansing Component for SSIS.
Clean, verify, standardize and format all your global contact data with Melissa's Global Contact Verify Component for SSIS.

Global Contact Verify Component

Use the Global Contact Verify Component to clean, verify, standardize and format all your global people data – name, address, email and phone. The component utilizes a USPS® CASS-Certified engine to return a complete and standardized U.S. address and even adds missing ZIP+4® data, missing suite and apartment numbers, and corrects spelling and formatting errors. Additionally, the component will verify addresses from 240+ countries, standardize addresses to local country format, and add missing postal codes, regions, etc. The component supports many different language sets and can transform non-Latin writing systems into Latin characters so addresses in foreign languages like Russian, Greek, Chinese, Japanese, and others can easily be validated.

The component will geocode international addresses for 40+ countries, providing a precise (rooftop) latitude/longitude coordinate for an address to power market segmentation, sales clustering, logistics, risk exposure, and more.

The component also does verification on your phone, email, and name data. Phone verification includes real-time lookup technology to distinguish between global landlines and mobile numbers, and validates the number is accurate, live, and callable. Caller ID will return the name and address associated with the billing contact.

Email verification capabilities include: real-time email mailbox verification to ensure an inbox is live; email syntax and domain correction; and FCC Mobile Domain Detection to ensure CAN-SPAM compliance.

Contact Verify Component (Personator)

The Contact Verify Component utilizes Melissa's Persontor dataset containing billions of records to validate for each provided element of a U.S. or Canadian contact record: name; address; phone; and/or email; and will match name-to-address for a simple and quick identity verification.

The Personator Component also offers a wealth of append functionality to enrich your contact records including:

  • Filling in missing contact information like business/consumer emails, addresses, phones and names.

  • Adding current addresses for customers and prospects that have moved in the U.S. and Canada – matching your records against a propriety database of address changes going back 20+ years. Note: this process does not satisfy the USPS Move Update requirement.

  • Enriching records with the most accurate Geopoints (lat/long coordinates) at the rooftop level for 95% of U.S. physical addresses (residences and businesses). Includes information on the County Name, FIPS Code, Census Tract, Block Groups, Block Numbers, and “Core Based Statistical Area (CBSA) and Metropolitan/Micropolitan areas for location intelligence.
Melissa's Contact Verify Component utilizes Melissa's Personator Dataset containing billions of record to validate.
A database containing duplicates result in waste and inefficiencies, Melissa's MatchUp Component can parse and standardize name and address to achieve a better customer view.
MatchUp can parse and standardize name and address info to consolidate non-matching records to achieve a single customer view for better lifetime value predictions.

MatchUp® Component

On average, a database contains 8-10% duplicate records. These duplicates result in waste and inefficiencies, and cloud your ability to get a single, accurate view of the customer. The MatchUp Component uses advanced fuzzy matching algorithms and deep domain knowledge of contact data to find even the hardest-to-detect U.S. and international (Canada, Europe, South America, Australasia, and more) duplicate records.

MatchUp employs over 16 different fuzzy matching algorithms to identify “non-exact matching” duplicate records that are difficult to uncover, including:

  • Phonetic Matching – detect “alike sounding” relationships
  • N-gram or Q-gram-based Algorithms – used in statistical natural language processing
  • Jaro-Winkler Algorithm – measure of similarity between two strings
  • MD Keyboard (proprietary) – counts keyboarding mishits and weighs the distance of the mishit
  • Containment – matches when one record has components contained in another record (“Smith” is contained in “Smithfield”)
  • Frequency – matches the characters in the components in one record to the characters in another without regard to the sequence (“abcdef” = “badcfe”)
  • Fast Near – typographical matching
  • Accurate Near – typographical matching (usually better results than Fast Near)
  • Frequency Near – Similar to Frequency, but allows you to specify how many characters may be different between components
  • UTF-8 Near
  • Vowels Only
  • Consonants Only
  • Alphas Only
  • Numerics Only - decimals and signs are considered numeric

The MatchUp Component also includes other matching capabilities for specific scenarios including:

  • Proximity Matching
    MatchUp’s patented distance algorithm uses lat/long coordinates and proximity thresholds to identify duplicate data.

  • Householding
    MatchUp can identify and consolidate records that are members of the same household. This is useful in being able to evaluate the total sales relationship and by eliminating unnecessary multiple mailings for cost savings.

  • List Intersection/Suppression
    MatchUp finds all the common data elements between multiple lists and/or use suppression to find just the data unique to each individual list.
Melissa's MatchUp Component also offers other matching capabilities for specific scenarios that you may have.
Based on location attributes, MatchUp can detect matching records at different addresses (for instance, a company with two different entrances) but within a specified distance to each other.
With SSIS, MatchUp has the unique capability to craft a Golden Record using proprietary survivorship guidelines.

Survivorship and the Golden Record

Within SSIS, MatchUp has the unique capability to create a Golden Record using proprietary survivorship rules. Most traditional rules-based approaches to survivorship use techniques involving either (1) the most recent, (2) the most frequent, or (3) the most complete. MatchUp can utilize these techniques, but it also provides the option of determining and consolidating the best possible record based on data quality rules. MatchUp will determine the validity of the data in each field so you can easily rank and select the surviving record based on the actual quality of the data. This technique for golden record selection offers the most effective and logical approach when it comes to survivorship

SmartMoverSM Component

The SmartMover Component provides change-of-address processing for U.S. and Canadian addresses. This helps you stay in touch with consumers and businesses that have moved, eliminate the costs associated with undeliverable-as-addressed mail, and qualify for applicable postal discounts.

For U.S. addresses, the SmartMover component matches your customer records against the USPS® full NCOALink® data file of 160 million moves going back 48-months. Processing your records utilizing the SmartMover component will satisfy the USPS Move Update requirement for a period of 95 days from the date of processing to qualify for First-Class and Standard Mail® discounts. Melissa is a NCOALink® Full Service Provider licensee of the USPS. NCOALink® processing requires a Processing Acknowledgement Form (PAF). Download a copy of our NCOALink PAF

For Canadian addresses, the SmartMover component will match your address file against the Canada Post NCOA® database containing over 11 million records over the last 72 months. Melissa is one of only a handful of Canada Post licensees. Canada NCOA processing requires a signed copy of the Canadian NCOA Acknowledgement Form. Download a copy of our Canadian NCOA form.

Melissa's SmartMover Component for SSIS provides change-of-address processing for U.S. and Canadian Addresses.

Demographic Component

The Demographic Component provides detailed consumer demographics from over 2 billion records containing 250 million individuals and 170 million households in the U.S. This valuable information offers you deeper insight into your customers, their behavior, and trends.

The Following variables can be added:

  • Date of Birth
  • Deceased Information
  • Gender
  • Presence of Children
  • Number of Adults
  • Marital Status
  • Home Owner/Renter
  • Household Income (range)
  • Length of Residence
  • Dwelling Type
  • Occupation

Property Component

The Property Component provides valuable property and mortgage data from over 140 million records for the U.S. Access variables from over 165 fields in categories such as: parcel; property address; owner; owner mail address; property values; current sale; current trust deed; prior sale; lot/land; square footage; building. For a complete list of data available click here.

Melissa's Property Component for SSIS provides valuable property and mortage data from 140 million records for the U.S.
IP Location for SSIS by Melissa provides the geographic location of an Internet Protocol IP Address. As well as a wealth of additional data.

IP Location Component

The IP Location Component provides the geographic location of an Internet Protocol (IP) address, including latitude, longitude, city, state, ZIP Code/Postal Code, region, hosting Internet Service Provider (ISP), connection speed and type, and domain name. This information helps you identify where your web visitors are coming from. This is useful for ecommerce sites where you might want to prepopulate country code on forms, display a different language, filter access from countries you don’t do business with, and/or reduce credit card fraud based on geographic location. IP Location can also help fight illegal spamming and hacking by identifying the location of the problem.

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