Intelligently integrate, link, and prepare data from virtually any source with DataMatch Enterprise – your software toolkit for code-free profiling, cleansing, matching, and deduplication.
Certified for security, quality, compliance, and code integrity.
Prepare Clean, Consistent Data Across the Enterprise
DataMatch Enterprise™ solution is a highly visual data cleansing application specifically designed to resolve customer and contact data quality issues. The platform leverages multiple proprietary and standard algorithms to identify phonetic, fuzzy, miskeyed, abbreviated, and domain-specific variations. Build scalable configurations for deduplication & record linkage, suppression, enhancement, extraction, and standardization of business and customer data and create a Single Source of Truth to maximize the impact of your data across the enterprise.
Check out how DataMatch Enterprise works
Data Discovery and Profiling
Profile your data to highlight potential cleansing opportunities.
The most important part of a data quality process is identifying potential problems in your organizational data. DataMatch Enterprise comes with an out-of-the-box profiling tool that quickly provides enough metadata to construct a cogent profile analysis of data quality across all datasets.
It highlights all cleansing, matching, deduplication, and standardization work that needs to be done to improve data quality. As the profile is generated within the same system that will be used to perform these activities, it becomes a central data cleansing hub for all kinds of data files.
Data Cleansing Done Right
Use our built-in libraries, proprietary matching capabilities, and sophisticated pattern recognition features to clean and standardize your data at scale. Our intuitive visual interface minimizes the number of clicks needed to complete a data cleansing and matching project, and is fully customizable according to your unique data quality project needs – both for real-time matching and batch-oriented.
With our instant data preview feature, you can also preview the data as it is being transformed using data cleansing functions.
Data Matching and Deduplication
Find exact and non-exact matches in your datasets, and configure survivorship rules.
DataMatch Enterprise employs robust, real-time data matching algorithms, that work specifically on the nature of your data. If your datasets do not contain unique identifiers, or the information cannot be used to hide personally identifiable information, DME implements proprietary algorithms for phonetic, numeric, domain-specific, and fuzzy matching.
Moreover, you can tune level and weight variables of these algorithms to ensure maximum accuracy and least number of false positives. Once you have the data match results, you can start deciding which records to eliminate or merge to build a single source of truth at your company.
Address Verification Module
Check the validity of physical mailing addresses present in contacts databases.
DME’s powerful Address Verification module corrects addresses automatically, adds missing information (such as a zip code or a suffix), and compares against a list of valid addresses to verify it. Once it is verified, you can enhance each matching address with geocoding information automatically and add ZIP+4 level latitude and longitude values for the best in mapping precision – while improving deliverability with LACSLink® to convert rural addresses to street style addresses automatically.
API Access for Real-Time DQM
Build custom applications and workflows using DME’s RESTful API.
All of DME’s data cleansing and matching features and functions are exposed through our standardized, RESTful API. You can simply access and integrate its benefits in any custom project to reap all the benefits in real-time, including intelligent searching and profiling of large datasets, splitting and casing names and addresses ,transforming and standardizing data values, applying phonetic, numeric, and fuzzy matching logic on data records, grading match results to make merge purge decisions, and more – all at unprecedented speeds.
Have a specific data quality problem in mind?
DataMatch Enterprise covers a wide variety of features to help you at every stage of your
data matching and cleansing process.
Highlight potential data quality issues like non-printable characters, missing data, mixed numbers, and letters, etc.
Instant Data Preview
See how your data changes with your data cleansing methods in real-time and create the best configuration.
Email Address Cleaning
Advanced email address cleaning feature finds errors and automatically suggests corrections.
Define a single ‘master’ record by choosing which duplicate survives and the field you want to merge on while capturing additional data in a separate field.
Merge the most complete information across duplicates, overwrite data from a master to other duplicates, and delete duplicates from your data sets.
Integrate virtually any data source across the enterprise (databases, CRMs, social media, file formats, email, Big Data repositories, etc.).
Schedule your projects to run once, on a recurring basis, on a defined schedule, or when an imported file is updated.
Automatically cleans telephone numbers to improve matching capability. Useful when matching international numbers.
Process millions of records with our highly scalable, in-memory architecture and export only when you are satisfied.
Match data across columns – useful when data entry errors put data in the wrong column.
Test and configure your data cleansing workflows and save them as reusable DataMatch projects.
Manipulate your data with advanced filtering functions like wildcards, and/or, or/not statements, etc.
Includes over 60,000 common names for standardization when matching. i.e. Danny becomes DANIEL, etc.
Identify and count unique words and values in your lists and so you can replace, delete, or extract values into new fields.
Set a match threshold (0-100%) and view your duplicates – match on multiple fields & see the match percentage on each field.
Use Regex wizard to quickly identify patterns and extract into new fields. Example: Text “3 x 4 x 6” can be extracted into: Length = 3, Width = 4, and Height = 6.
Built-in libraries for nicknames (Jon=Jonathan), postal codes, street suffixes, state and city, and a best-in-class library creator for your custom needs.
Trusted by the World’s Best Organizations
“My Go-To Database Tool; Saves Time, Increases Efficiency”
“DataMatch Enterprise is easy to learn and use. It’s easy to review results. Saves us tons of time in manually checking records.”
Business Development Associate, St. John Associates
“DataMatch Enterprise – Powerful and Easy to Use”
“It does a great job with data cleansing making the matching process even more powerful and being able to merge rows with very flexible rules for the final export is extremely helpful.”
Platform Architect, Worldpay
“Best product ever.”
“It makes our matching projects in a short amount of time and helps prove ROI to our clients.”
Satisfaction Manager, RentPath
Fuzzy Matching 101: Cleaning and Linking Messy Data
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