Data Cleansing Software
Generate accurate business insights, increase confidence in your data, and boost productivity with data cleansing software rated faster and more accurate than IBM and SAS.
Rated Fastest and Most Accurate Data Cleansing Software
| Features of the solution | Data Ladder | IBM Quality Stage | SAS Dataflux | In-House Solutions | Comments |
|---|---|---|---|---|---|
| Match Accuracy (Between 40K to 8M record samples) |
96% | 91% | 84% | 65-85%* | Multi-threaded, in-memory, no-SQL processing to optimize for speed and accuracy. Speed is important, because the more match iterations you can run, the more accurate your results will be. |
| Software Speed | Very Fast | Fast | Fast | Slow | A metric for ease of use. Here speed indicates time to first result, not necessarily full cleansing. |
| Time to First Result | 15 Minutes | 2 Months+ | 2 Months+ | 3 Months+ | |
| Purchasing/Licensing Costing | 80 to 95% Below Competition | $370K+ | $220K+ | $250K+ | Includes base license costs. |
Note: in-house implementations have a 10% chance of losing in-house personnel, so over 5 years, half of the in-house implementations lose the core member who ran and understood the matching program.
*Above tests were completed on 15 different product comparisons with university, government, and private companies (80K to 8M records). This includes the effect of false positives.
What You Get with Our Data Cleansing Software
Unmatched Speed
and Accuracy
Unparalleled matching accuracy and speed for enterprise-level data cleansing beating IBM and SAS.
Big Data
Capability
Seamless integration with MongoDB and Hadoop-based databases for processing of 100 million+ records.
Proprietary Matching
Algorithms
Mix of established and proprietary matching algorithms with a high level of matching accuracy.
Code-Free
Matching
Designed for both business and IT users, DataMatch allows you to match and cleanse data visually.
What is Data Cleansing?
Data cleansing, also known as scrubbing and wrangling, is a data quality process that allows your business to improve the accuracy and usability of your data by resolving errors, enriching it, and providing a standardized, consistent result.
Issues are resolved by determining matches within and across data sources, deduplicating, merging linked records, filling in missing information, correcting spelling mistakes, parsing and correcting contact information such as email address, postal address and phone number, and picking up on variations and nicknames to detect matching records.
Those new to data cleansing often use the basic “find and replace” or regex functions through text editors, or may use spreadsheets to sort and aggregate data. These old-school methods take an enormous amount of time and energy and don’t capture all the errors and inconsistencies found in large data sets.
You need a better, modern approach to data cleansing.
You need Data Ladder
Transform Dirty Data
To Deduplicated, Cleaned and Merged Data
Our industry-leading data cleansing software helps you find matching records, merge data, and remove duplicates using intelligent fuzzy matching and machine learning algorithms, regardless of where your data lives and in which format.
Improve your data quality with data cleansing and make it your competitive advantage.
How Can Data Cleansing Software Help You Grow Your Business?
Data cleansing software helps you make the right decisions, improves efficiency and productivity, increase sales, and helps you leapfrog the competition. Clean and accurate data across your organization translates to accurate analytics and all-around business intelligence. Visualize linkage statistics, generate reports, identify trends, and be confident that your decisions are based on clean, accurate data. Standardized data allows your business to work better and faster because your data is always readily usable with data cleansing software designed for both business and IT users.
Better Sales Intelligence:
Your sales team will be able to work faster and better because they will have accurate and complete information on prospects.
Improved Customer Relations:
Avoid poor experiences by consolidating customer information and making it available to your frontline support staff.
Integrate Your Data:
Combine, match, and deduplicate across file formats (.xlsx, .txt, .xml, .json, etc.), databases, CRMs, social media, and Big Data.
Generate Better Insights:
Cleaning and matching across data sources allows you to generate insights and business intelligence based on complete, accurate data.
Understand Your Data:
Drill down into your data visually and see what you need to focus on most for immediate ROI improvements.
360-Degree Views for Personalization:
Enable hyper-personalized communication by exploiting every possible linkage opportunity to build a clean and consistent 360-degree customer view.
Uncover Hidden Relationships:
Cleanse your data at scale to match seamlessly across the enterprise and uncover hidden linkage opportunities.
Boost Employee Productivity:
Combine data like performance reviews, feedback forms, and attendance to enhance employee performance.
Higher Efficiency:
Clean and link your data to eliminate hidden data factories that, according to IBM, results in losses of $3.1 trillion in the US.
Data Preparation for Your Data Lake:
Blend virtually any Big Data source and clean intuitively and power your business analytics with clean, consistent information.
In a nutshell, data cleansing will help you improve
Operational
Efficiency
Lead
Generation
Business
Visibility
Customer
Experience
With Data Ladder, You Get:
Fully visual, intuitive interface
Complete set of data cleansing tools
Affordable package; costs 95% less than comparable solutions
Semantic matching for unstructured data
Support for disparate data sources for record linkage
I want to improve
customer acquisition
Manage multi-channel customer data with confidence and increase marketing effectiveness.
I want to make
better decisions
Clean data to support all-around business intelligence to decide and execute with confidence.
I want to reach
the right people
Verify and correct address data while adding geocodes and demographic data in bulk.
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