data engineering apis

Data Cleansing and Data Enhancement Services with our Proprietary, Machine Learning-based Toolset


Can you trust your important data assets?

Clean My Data

Free Data Quality and Data Usability Assessment

Data can be inconsistent, redundant, incomplete, and difficult to match, standardize, validate, and process.

The challenge is that it can be difficult to know if any of these or other data quality issues exist within your various data assets, and if so, to what extent and what can be done about them. If there are data content exceptions and quality issues, they could be affecting analytics, reporting, data-driven processes, customer communication, data science initiatives, and a whole lot more - not to mention missed opportunities because your data assets are a shell of what they could be. That's not good and results in a poor ROI with current data investments.

This is why we provide free data quality and data usability assessments. We will analyze some portion of your data (perhaps a single dataset, a few columns, multiple databases - you choose whatever makes sense) and then let you know what we find. If we don't find any (unlikely) data quality or data usability issues, or we do find some issues of minimal consequence in your opinion (possible), then you can rest assured your data is in pretty good shape. If we do find any significant issues, we will share them with you and then outline how we can help you with these challenges. At that point, it will be up to you to choose whether or not to work with us. Fill out the form and will be in touch.

So if you need a data partner to help with your data processing challenges, including multi-pass data matching, data engineering, data standardization or database building, let us put our decades of data analysis and processing experience and innovation to use on your behalf. Let's do an assessment right away!

Some examples of what we can do to help:

✔ Matching data across different and heterogeneous sources
✔ Eliminate data redundancy and duplicate data
✔ Identify inconsistently represented data content
✔ Standardize data for accurate analysis
✔ Merge data from internal sources
✔ Match data from external sources
✔ Verify data for accuracy
✔ Consolidate duplicate customer or prospect information
✔ Re-engineer data per requirements
✔ Database building from multiple sources
✔ Data quality analysis
✔ Enrich data from additional sources

Inconsistent data provides inaccurate analysis and redundant data can result in substantial costs ands missed opportunities. And that's just the beginning. We can help transform and re-engineer data using our experience combined with our proprietary tools, contextual Machine Learning-based processes, and advanced data processing capabilities. These innovative data tools, built on decades of experience and at the heart of our capabilities, are not available with anyone else.

Contact us using the form to learn more and to discuss your requirements. We can analyze data samples free of charge. Below are some samples of the types of challenges we can help resolve.



Request more info about the Free Assessment or other data topics:



Sample Organization Name Matches:

IBM
International Business Machines
i.b.m. corp

U-Haul
Uhaul Trailers

Costco Stores
cost-co

McKeson Corp
Mackesson
The Mckesson company

Florida St
Florida State University

Well's Fargo Bank
Wells Fargo

Nationwide Insurance
Nation Wide Ins.

PFIZER INC
Fizer

Forever 21 Inc.
FOREVER TWENTY-ONE

Biogen Pharma
The Biogen Corp

Apple
apple computer
apple comp
APPLE MOBILE
Apple International
apple inc.
Apple Stores
THE APPLE STORE
Apple Corp
Apple USA

7-11
7-eleven
Seven Eleven Stores
Seven 11 Inc.

Hilten Hotels
HiltonHotels
Hillton Resorts Inc.

Sample Individual Name Matches:

Bill Jameson
William R. Jamison

Dr Fred Johnston
Frederick P Johnson

Sallie Harrell
Sally Harrel

Jim Donaven
James Donovan

Gavin McMillan
Gaven P. MacMillen III

Elizabeth Donnelly
Liz Donley

Bob Ford
Robert Forde

Frank Menendez
Mr. Franklin Menendes

Lori Greenberg
Ms Laura J Greenburgh

Julia Rodgers
Julie Rogers

LINDSAY SCHROEDER
Lindsey Shrader

Pete Cellars
Peter Sellers
Petr R. Selars

tracy vasquez
Tracie Vasques

Kenny Vonn Jr.
KENNETH VAUGHN

Sample Address Matches:

100 East Main Street
100 E MAIN
100 E. Main St.

Park Ave #500
500 PARK AVENUE

745 BROADWAY AVE NORTH WEST APT 201
745 Broad Way N.W. Unit 201

400 Johnston Road #207
400 Johnson Rd Apt 207

PO Box 511
post office box #511

326-A Leigh Estates
326A Lee Estates


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