profiler object - melissa · if you're not continuously monitoring and assessing your data,...

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Looking to bring data quality analysis to data contained in columns? Look no further than Profiler Object from Melissa Data. Profiler analyzes new data before its merged into a data warehouse, and then helps ensure data quality once it has been warehoused. Profiler Object is a multiplatform API designed to analyze data in a variety of column types to ensure it adheres to the limitations imposed by the user-specified type. Profiler Object provides a great number of statistics, at varying levels of details, allowing users to develop informed strategies on how best to manage and employ their data. Profiler Object was designed to tackle two possible scenarios: Discovery In this scenario, Profiler analyzes new data before it's inserted into a data warehouse. It ensures the data is correctly fielded, consistently formatted, standardized, etc. Detecting and fixing data problems before data is merged into a data warehouse saves time and money. Monitoring It is difficult to maintain a comprehensive set of business rules in a data warehouse that supports multiple methods of access (Web, desktop, tablet, phone, etc.). Profiler addresses this problem by continually analyzing the warehoused data to ensure data quality. Understand Data Quality Issues Clearly & Quickly Profiler Object Easily Analyze the Quality of Data in Columns Features: • Allows regexes & error thresholds to be set for full-fledged monitoring • Uses sophisticated matching to output fuzzy and exact match counts • Available as a commercial C++ Data Profiler API that can be OEM’d into custom apps • Brings data quality analysis to data contained in columns Benefits: • Discover existing weaknesses in your database (duplicates, badly fielded data, bad data, etc.) • Create a metadata repository that aids in data governance and building strategic datamarts • Maintain data quality by continuously monitoring data after it’s merged into a data warehouse • Enforce business rules on incoming records, so you can maintain data standardization Profiler can analyze a wide variety of data types: • Contact Name • Title or Department • Company • Address • City • State or Province • ZIP™ or Postal Code • Country • Phone • Email Address If you are using the “state” field, for example, you can easily see all values in that field ordered in an ascending or descending order. This ordered data can be used by organizational leaders to improve business intelligence efforts. Knowledge-Based Analysis MA CA Value Count 100 76 ME 25 TX 18 NJ 15 MO 7

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Page 1: Profiler Object - Melissa · If you're not continuously monitoring and assessing your data, you are missing a critical piece of the data quality circle. This is why we created Pro˜ler

Looking to bring data quality analysis to data contained in columns? Look no further than Pro�ler Object from Melissa Data. Pro�ler analyzes new data before its merged into a data warehouse, and then helps ensure data quality once it has been warehoused.

Pro�ler Object is a multiplatform API designed to analyze data in a variety of column types

to ensure it adheres to the limitations imposed by the user-speci�ed type. Pro�ler Object

provides a great number of statistics, at varying levels of details, allowing users to develop

informed strategies on how best to manage and employ their data.

Pro�ler Object was designed to tackle two possible scenarios:

Discovery

In this scenario, Pro�ler analyzes new data before it's inserted into a data warehouse. It

ensures the data is correctly �elded, consistently formatted, standardized, etc. Detecting

and �xing data problems before data is merged into a data warehouse saves time and money.

Monitoring

It is di�cult to maintain a comprehensive set of business rules in a data warehouse that

supports multiple methods of access (Web, desktop, tablet, phone, etc.). Pro�ler addresses

this problem by continually analyzing the warehoused data to ensure data quality.

Understand Data Quality IssuesClearly & Quickly

Profiler ObjectEasily Analyze the Quality of Data in Columns Features:

• Allows regexes & error thresholds

to be set for full-�edged monitoring

• Uses sophisticated matching to

output fuzzy and exact match counts

• Available as a commercial C++ Data

Pro�ler API that can be OEM’d into

custom apps

• Brings data quality analysis to data

contained in columns

Bene�ts:

• Discover existing weaknesses in

your database (duplicates, badly

�elded data, bad data, etc.)

• Create a metadata repository that

aids in data governance and building

strategic datamarts

• Maintain data quality by

continuously monitoring data after

it’s merged into a data warehouse

• Enforce business rules on incoming

records, so you can maintain

data standardization

Pro�ler can analyze a wide variety of data types:

• Contact Name • Title or Department • Company • Address

• City • State or Province • ZIP™ or Postal Code

• Country • Phone • Email Address

If you are using the “state” �eld, for example,

you can easily see all values in that �eld ordered

in an ascending or descending order.

This ordered data can be used by organizational

leaders to improve business intelligence e�orts.

Knowledge-Based Analysis

MA

CA

Value Count

100

76

ME 25

TX 18

NJ 15

MO 7

Page 2: Profiler Object - Melissa · If you're not continuously monitoring and assessing your data, you are missing a critical piece of the data quality circle. This is why we created Pro˜ler

>> GET A FREE QUOTE: www.MelissaData.com/pro�ler

Looking for a way to continuously monitor and analyze your data quality? Get started today by requesting a free trial of Pro�ler Object.

About Melissa Data Corp.

Since 1985, Melissa Data has been a

leading provider of data quality and

address management solutions.

Melissa Data’s data quality software,

Cloud services, and data integration

components verify, standardize,

consolidate, enhance, and update

U.S. and global contact data,

including addresses, phone

numbers, and email addresses for

improved communications and ROI.

More than 10,000 companies

worldwide rely on Melissa Data to

gain and maintain a single, accurate

and trusted view of critical

information assets.

Melissa Data Corp.

22382 Avenida Empresa

RSM, CA 92688-2112

1-800-MELISSAwww.MelissaData.com

Find us on:Twitter: @melissadata

Facebook.com/melissadata

linkedin.com/company/melissa-data

© 2015 Melissa Data Corp. 012915

Free Trial - Pro�ler Object

Technical Specs

API Platform: Library available for Windows 2003/2008/7/Vista; Red Hat

Monitor, Measure & Analyze Data with Pro�ler Object

Melissa Data's Pro�le Object closes the loop on data quality. Your organization may be

working hard to clean and enhance data, and consolidate records. If you're not

continuously monitoring and assessing your data, you are missing a critical piece of the

data quality circle. This is why we created Pro�ler Object. When you employ Pro�ler, you

can expect to enjoy the bene�ts of quality data, including improved business intelligence

e�orts and more e�ective marketing campaigns.

Completing the Data Quality Circle

Available as a Data Quality Component For SSISYou can also experience the powerful capabilities of Pro�ler Object as a Data

Quality Component for SQL Server Integration Services.

Learn more by going to: www.MelissaData.com/ssis