Data cleansing software

Q: Why do you need a data cleansing tool?

Keep your data error-free, preserve data usability, benefit from data-driven initiatives, ensure data compliance, improve brand loyalty & stay relevant and up-to-date.

Q: What do get from DataLadder's data cleansing software?

With DataLadder's data cleansing tool, you can remove or replace empty values, leading and trailing spaces, specific letters or numbers, non-printable characters, and more.

A feature-rich toolkit 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.

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DEFINiTION

What is data cleansing?

Data cleansing is the process of fixing incorrect and invalid information present in databases, and achieving a consistent and usable view across all disparate sources.

This process usually consists of eliminating incorrect values, validating the format and pattern of data values, using appropriate data types, putting min/max character limit, and more.

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 can do for you?

Removals and replacements

With DME’s data cleansing tool, you can remove or replace empty values, leading and trailing spaces, specific letters or numbers, non-printable characters, and more.

Parsing and merging columns

Run data fields against a dictionary of words to identify its sub-data elements (such as Street Name and Number for Address), and merge columns to follow custom-created formats.

Transforming letter cases

DME offers various features for transforming cases of letters in strings, ensuring a consistent and standardized view across all data sources.

Building and recognizing patterns

Use DME’s extensive pattern library while data profiling and data standardization. It offers the ability to identify valid and invalid values, as well as transform data fields to follow a defined pattern (a technique widely used for masking personally identifiable information (PII)). DME also offers a visual, drag and drop regex designer for creating custom patterns.

Working with commonly used words

With DME’s wordsmith tool, you can fetch the most repetitive words occurring in a data field, and decide to flag, replace, or delete certain words to achieve standardization, and prepare data for matching and deduplication.

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.