Extract, Transform, Load (ETL)

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Extract, transform, and load processes (ETL) draw existing data from multiple sources, perform necessary operations such as normalization and optimization on it, and load the processed data into a new warehouse or database. Our ETL database services include data migration to simplify platform upgrades, standardization to make sure all your valuable data is usable, de-duplication to eliminate redundant records, and validation to preserve your records from data decay.

DATA STANDARDIZATION | DUPLICATE IDENTIFICATION | DATA VALIDATION | DATA MAPPING

DATA STANDARDIZATION

[defined as]: Putting existing data into standardized or normalized formats for ease of use and accurate analytics

Service Benefits

Service benefits: Groups of data share a common format. We see it in ZIP codes, phone numbers, and lists of names; it’s part of how we recognize these everyday data points. When data doesn’t fit an established format, it needs to be standardized to be accessible. Our data standardization services make previously sequestered information accessible and define protocols to handle incoming data so your database stays fully synchronized and usable.

Retain the value of legacy data by standardizing it
Keep incoming data organized automatically
Manage data migration with ease
Transform multi-platform records into unified, cohesive data sets

DUPLICATE IDENTIFICATION

[defined as]: Finding and marking multiple copies of the same or similar records for merging or elimination

Service Benefits

Service benefits: It’s easy to introduce duplicate records but challenging to remove them from the system. It starts with establishing a unique identifier to each individual, each company site and each household. Once this is established we eliminate all of the duplicate records and erroneous variations of businesses that hinder your ability to market effectively.

Track prospect and customer records over time
Maintain accurate contact and demographic data by eliminating redundancy
Merge incomplete files to get a detailed portrait of your prospects
Improve analytical accuracy

WHITE PAPER

Developing Your Data Management Playbook

Centralize, normalize and optimize your data.

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DATA VALIDATION

[defined as]: Checking records against an established benchmark or constraint to ensure accuracy, consistency, and usability

Service Benefits

Invalid data is costly. Our validation services measure data against some of the most reliable yardsticks in the industry, including the U. S. Post Office’s National Change of Address (NCOA) database, CASS, email ping, spam identifier and hard-bounce table through our ReachVerify process, a rigorous multi step process. We regularly update your records to keep email and direct mail deliverability high. We work with you to develop validation rules that retain as much useful data as possible while eliminating or archiving information that no longer contributes to a deeper understanding of your audience.

Improve prospect and customer access with higher deliverability and contact rates
Earn the trust of email service providers by using properly validated contact data
Keep data quality consistently high
Save effort on data collection and maintenance by validating existing information

WHITE PAPER

Data Science Capability Maturity: A Self-Assessment

Pinpoint your organization’s current data science capabilities

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DATA MAPPING

[defined as:] Establishing the relationship between data points from two or more data sets and consolidating them within a master database.

Service Benefits

Data mapping provides a unified view of the data in the Database. Complex Databases which have multiple sources of information need clearly defined processes of identifying common data points and transforming that data so it is actionable across the Database. We develop relationships between data fields and transform data sets into the building blocks of sophisticated analytics. With database mapping, you see the deeper connections between collections of data as a whole.

Link disparate data sets together in logical ways
Define the relationships that underlie your database
Get a clear picture of how your data interacts
Gain improved access to data through standardized and master field unification

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