data quality components - melissa 1-800-635-4772 melissa data is a complete global data quality...

Data Quality Components

for SSIS

Global Contact Data Quality Tools for MDM Success

2 1-800-635-4772 www.MelissaData.com

Melissa Data is a complete global data quality solutions provider with offi ces in the U.S. and international locations in the U.K.,

Germany, Australia, and India. Our smart sharp data cleansing tools support all Microsoft® technologies including SQL Server®

Integration Services (SSIS), Data Quality Services (DQS), the Azure™ Marketplace, .NET, Dynamics, and Excel®.

Since 1985, Melissa Data has helped businesses of

every size achieve the highest level of data accuracy

and completeness at the most affordable price.

More than 10,000 companies worldwide rely on

Melissa Data to gain a single, accurate, and trusted

view of critical information assets.

Melissa Data – Your Partner in Global Data Quality

Melissa Data Across the World

Rancho Santa Margarita, CA

Corporate Headquarters Operations

Braintree, MA

Raleigh, NC

Rockwall, TX

Seattle, WA

Wilsonville, OR

Bangalore, India

Berlin, Germany

London, UK

Sydney, Australia

Melissa Data supports customers in their local time with 6 offi ces in the

U.S. and regional offi ces in Berlin, Bangalore, London, and Sydney.

3 www.MelissaData.com 1-800-635-4772

The Impact of Bad Data on Your BusinessDid you know that 91% of businesses suffer from common data errors? The high percentage isn’t surprising, given the fact that your

data goes stale over time. Experts say up to 2% of records in a customer file become obsolete in just one month due to divorces,

marriages, moves, or even deaths. In fact, 17% of Americans (45 million people) change addresses each year, according to the

USPS®. So, if you aren’t cleaning your contact data regularly, you are losing contact with some of your best customers.

This data decay affects the accuracy and usefulness of data

used for communications, analytics, and compliance –

and puts your company at a competitive disadvantage.

This is what your company is up against – the threat of

dirty data disrupting your operations, corrupting the single

view of your customer – and ultimately harming your data

warehousing and business intelligence initiatives.

Simply put, bad data is bad for your business.

25%of companies’ data is bad**

20%of labor/productivity

is affected*

40%of business projects fail due to bad data*

Here’s a good hard look at the hidden costs of bad data.

** SiriusDecisions *Gartner, Inc.


A Full Spectrum of Data QualitySo now you know the damage.

Remember, data quality isn’t a one-time fix. It is a process that must be repeatedly employed to maintain good quality data. Data gets stale

through time, even after a good scrubbing.

Here’s the solution – implement a continuous process

that addresses the full spectrum of data quality –

from profiling data to identify weaknesses,

to cleaning, enriching, and matching.

We provide all of these capabilities in ONE solution –

Data Quality Components for SQL Server Integration

Services (SSIS).

The full spectrum of data quality delivers clean, quality data for MDM,

business intelligence, enterprise data warehousing, and Big Data success.

PROFILEMEASURE

MONITOR

PARSE

STANDARDIZE

CLEAN

ENRICH

MATCH

DEDUPEMatch& Dedupe

Data Profile & Monitor

Data Verify & CleanData Enrich


Data Quality Components for Microsoft®

SQL Server® Integration Services (SSIS)Our Data Quality Components for SSIS offers the full spectrum of data quality – an all-in-one solution featuring custom data cleansing

transforms to cleanse, update, consolidate, and continuously enrich your contact data. Here are the processes in the solution that support

the entire lifecycle of data quality:

Profi ler Transform

Identify problems and weak points with your data beforehand.

Contact Verify, Global Verify, Personator® & SmartMover Transforms

Verify, correct, and standardize your data to ensure it’s accurate, reliable, up-to-date, and complete.

Personator Demographics, IP Locator & Property Transforms

Get greater insight into your data with more detailed information to improve customer contactability.

MatchUp® Transform

Flag duplicate records using powerful fuzzy matching algorithms.

MatchUp Transform

Eliminate duplicates and identify the best overall record to get a single, accurate view of your data.

PROFILE

CLEAN

ENRICH

MATCH

DEDUPE

SM


Know exactly what your system’s data quality issues are right at the start, clearly and quickly – before any data-driven initiatives are

executed. Profi ling your data is that critical fi rst step in assessing the quality of your data and continuously monitoring it over time.

Profi ler® TransformPROFILE

Monitor, Measure, and Analyze Your Data with Data Profi ling


Monitor, Measure, and Analyze Your Data with Data Profi ling

Our new Profi ler transform analyzes data in a variety of column types to ensure it adheres to the limitations imposed by the user.

It will also provide statistics, at varying levels of detail, to allow users to develop informed strategies on how best to manage and

employ their data. This helps minimize costs by pinpointing problems in your data before it’s merged into a data warehouse or

launch your next campaign.

• Discover existing weaknesses in your database

(duplicates, badly fi elded data, etc.)

• Supports building a target schema with sizes, nulls,

unique counts, length, and fi eld identifi cation

• Maintains data quality by continuously monitoring data

after it’s merged into a data warehouse


Ensure you have the most accurate, clean and lean database around. Our Contact and Global Verify transforms will correct,

parse, standardize, and geocode U.S., Canadian and international addresses, names, phone numbers, and email addresses for

improved data integration, business intelligence, and CRM initiatives. The Global Verify transform will transliterate many character

sets and displays output in either native or Roman characters, correct misspellings, and convert data to the local format.

• Verify, correct, and standardize addresses for 240+ countries and territories

• Real-time global Email Mailbox Verifi cation eliminates 95% of bad emails

• Verify and normalize U.S. and Canadian phone numbers on a 7-10 digit level

• Parse names, genderize, and detect suspicious words or companies in

name fi eld

• Geocode U.S. addresses by assigning rooftop lat/long coordinates

Contact & Global Verify TransformsCLEAN Verify and Standardize U.S. and International

Contact Data


Verify and Standardize U.S. and International Contact Data

Roughly 20% of the data in a company’s database is incorrect or outdated, resulting in returned mail and address correction fees.

Update the addresses of U.S. and Canadian customers that have recently moved before you mail with SmartMover to reduce

wasted postage associated with undeliverable-as-address (UAA) mail.

SmartMover updates addresses using of the following databases:

• USPS® NCOALink® - Contains more than 160 million change-of-address

records fi led in the last 48 months.

• Canada Post NCOA® – The most up-to-date information available on

changes of address fi led by Canadian households and businesses

over the previous 72 months.

SmartMover TransformReduce Undeliverable Mail and Shipments with Updated Addresses

CLEAN

SM


Achieve a whole new level of accuracy and completeness using Personator’s powerful name-to-address matching and retrieval

technologies and multisourced data. Personator verifi es that each contact data element – name, address, phone, and email

information – belongs together for identity authentication and fraud prevention. Personator gives you the confi dence that your

contact data is the most relevant, complete, and up-to-date.

• Prevent fraud by verifying identity

• Increase effectiveness of marketing efforts with

complete contacts

• Eliminate costs associated with returned shipments and mail

• Enrich records with missing contact, geographic, and

demographic info

Personator® TransformENRICH Clean, Correct, and Complete Your Contact Data

CLEAN


Personator® TransformClean, Correct, and Complete Your Contact Data

[email protected]

Demographics

Household Income: $15,001-$20,000Length of Residence: 5-6 YearsOwn/Rent: De�nite Renter

Address

Email

Name

New Address

John Wayne Brown

22382 Avenida EmpresaRancho Santa Margarita, CA92688-2112

50 EnterpriseAliso Viejo, CA92656-1153

Capabilities include:

• Check – Determine the validity of each data point independently

• Verify – Authenticate the record by matching name to address, email, or phone

• Append – Add missing contact info like name, address, phone, email

• Move – Update records with the most current address for person or business based

on 10+ years of history – no mailing requirement

• Demographics – Add valuable info such as birth date, number of children,

marital status, gender, household income, resident type, Tiger Census, and more


Enrich your data with additional demographic, lifestyle, property, and IP location information to gain deeper insight into your customers, identify trends, market better to prospects, and extract greater value from your database.

Personator® TransformENRICH Enrich Your Database with Demographics

Demographics

Add valuable information such as birth date, number of children, marital status, gender, household income, resident type, and more.


Enrich Your Database with Demographics

Property

Access comprehensive property and mortgage data for over 140 million properties in the U.S., including owner information, property values, current sale information, and more.

IP Locator

Determine the physical location of an IP address to identify an Internet user’s geographical location, including country, region, city, lat/long, postal code, and domain name.

IP Locator & Property TransformsENRICH


The average database contains 10% of duplicate records, creating a costly business problem. Identify the most difficult-to-detect duplicate records using MatchUp’s advanced fuzzy matching algorithms and deep domain knowledge to gain a more accurate, single view of your contact data and dramatically increase the effectiveness of your data mining or business intelligence initiatives.

MatchUp® Transform

MATCH

Identify and Eliminate Hard-to-Detect Duplicate RecordsDEDUPE

• Proximity Match Set geographic distance as the matching criteria to group records that are geographically close.

• Domain Knowledge Build rules and logic to handle numerous contact data idiosyncrasies such as address obscurities, nicknames, abbreviations, company keywords, suffixes, and different formatting.

• Fuzzy Match Link related records with fuzzy algorithms and match thresholds. Output matches, possible matches, and non-matches based on desired threshold.

• Householding Group data by pre-defined criteria that is often a household (all members of a house count as one group). The concept can be applied to a department, last name, etc.

• List Intersection/Suppression Find all common data between multiple lists. Use List Suppression to find just the data unique to each individual list.

Capabilities include:


Identify and Eliminate Hard-to-Detect Duplicate Records• Golden Record/Survivorship Melissa Data’s unique approach to determining the most accurate view of the customer – known as the Golden Record – is based on a relevant data quality score derived from the validity of data such as address, phone number, email, and name. Most businesses use generic survivorship rules, but unlike its competitors, Melissa Data incorporates reference data to identify the best record based on several criteria – most complete; best overall quality; and most frequent.

During this survivorship process, duplicate entries are collapsed into a single customer record while retaining any additional information that may also be accurate and applicable.

The Golden Record selection criteria of the best Data Quality Score (based on Name, Address, and Phone) would select the second record as the Most Complete.

The Survivorship process allows you to gather column data from one duplicate and gather another column value from another record. In this graphic, incomplete matching records – the most recent sales date (Last Visit) and the highest purchase amount (Sale Amount) – are collapsed to fill in the blanks – to form a complete, accurate, single record.

Example: The following three records are duplicates.

Worldwide Technical Support

Free Worldwide Technical SupportWe support developers and DBAs by offering source codes, a

120-day ROI guarantee, and free unlimited technical support to

meet any need.

Full Feature Free Trial or a Free Community Edition We offer a free trial for our Data Quality Components for SSIS

with all features included. We also offer a free Community

Edition with limited profi ling, matching, and parsing capabilities.

No license required.

http://www.melissadata.com/editions

Download a free trial now!

www.MelissaData.com

data quality components - melissa 1-800-635-4772 melissa data is a complete global data quality...

Documents