Data cleansing software
Our data cleansing tool is feature-rich solution that helps you to eliminate inconsistent and invalid values, create and validate patterns, and achieve a standardized view across all data sources, ensuring high data quality, accuracy, and usability.
Trusted By
Trusted By
DEFINiTION
What is a data cleansing tool?
A data cleansing tool is a solution that helps eliminate incorrect and invalid information from a dataset, and achieve a consistent and usable view across all data sources. Some common data cleansing and standardization activities include:
- Removing and replacing empty or garbage values,
- Parsing aggregated columns to identify smaller sub-components,
- Transforming letter cases,
- Merging the same or similar columns together to avoid duplicates,
- Transforming values to follow the correct pattern and format,
- Flagging, replacing, or eliminating the most repetitive words in a column to remove noise in bulk.
Benefits
Why do you need a data cleansing tool?
Keep your data error-free
Remove missing, incomplete, and invalid values to avoid major roadblocks in the execution of business processes.
Preserve data usability
Presence of data doesn’t guarantee data usability; improve data adaptability with a clean and standardized dataset.
Benefit from data-driven initiatives
Make the best decisions for your business by using clean and reliable data sources and gain true business insights.
Ensure data compliance
Ensure that your data management strategies comply to data compliance standards, such as such as GDPR, HIPAA, CCPA, etc.
Improve brand loyalty
Perform CRM data cleansing and leverage accurate information to offer personalized experiences to customers.
Stay relevant and up-to-date
Run quick data quality checks with an easy-to-use and inexpensive data cleansing tool for staying relevant and up-to-date.
Features
What DME’s data cleansing tool can do for you?
There’s more
What else do you get out of the box?
Our data cleansing solution comes with a number of in-built features that facilitate easy, automatic, and cost-effective data cleansing operations at any time.
- Live preview of cleansed data
- Data type identification
- Pre-built & custom patterns
- Scheduler for automatic data cleansing
- Proper case transformation
- Dictionary of common words
- Custom filters for personalized view
- Multi-format support for exporting results
User roles
A tool made for everyone
Data analysts
Business users
IT Professionals
Novice users
Features
We take care of your complete DQM lifecycle
Import
Connect and integrate data from multiple disparate sources
Profiling
Automate data quality checks and get instant data profile reports
Cleansing
Standardize & transform datasets through various operations
Matching
Execute industry-grade data match algorithms on datasets
Deduplication
Eliminate duplicate values and records to preserve uniqueness
Merge & purge
Configure merge and survivorship rules to get the most out of data
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
Oops! We could not locate your form.
Mastering Data Integrity: How Record Linkage Can Transform Security and Investigations
With data breaches exposing more than eight million records worldwide just within the last quarter of 2023, an average data breach costing around USD 4.45
12 Challenges in Financial Data Migration and How IT leaders Tackle Them
12 Challenges in Financial Data Migration and How IT leaders Tackle Them Data migration projects are notorious for either going over budget or failing to
Mastering Data Integrity: How Record Linkage Can Transform Security and Investigations
With data breaches exposing more than eight million records worldwide just within the last quarter of 2023, an average data breach costing around USD 4.45
12 Challenges in Financial Data Migration and How IT leaders Tackle Them
12 Challenges in Financial Data Migration and How IT leaders Tackle Them Data migration projects are notorious for either going over budget or failing to
The Impact of Data Quality on Financial System Upgrades
The Impact of Data Quality on Financial System Upgrades Imagine losing 31% of your revenue due to poor data quality. For financial services, this isn’t