Data Quality Audit Solutions
Our data quality experts will amaze you with how quickly and inexpensively they can assess the quality of your data.  Our Applaud software reduces the time and cost of data quality projects by at least 50% compared to every other alternative.

Data Quality is Crucial
The importance of data quality cannot be overstated.  Data quality problems can risk the success of data migration projects, data integration projects, business intelligence projects, data warehouse projects, system implementation projects, and the most important of all IT responsibilities - day-to-day operations.  Your business depends on data.  If the quality of your data is poor, you can steer your business in the wrong direction.


The Only Rapid Application Development (RAD) Solution
Our Data Quality solutions are based on our proprietary software product, Applaud.  Applaud is the only Rapid Application Development (RAD) tool designed for data quality projects.  Applaud's unique tools dramatically speed the process of identifying and correcting data quality problems.  Applaud solutions are delivered in less than half of the time and cost of other alternatives.

Learn more about Applaud’s RAD design...


"Exceeded my expectations tenfold!"

Project Manager
Global consulting firm

  The Only EPACTL Tool
Applaud is the only "EPACTL" tool - the only single software product with integrated tools to extract, profile, analyze, cleanse, transform and load data.  EPACTL is a new breed of software that provides integrated tools to accomplish all requirements of data quality and data migration/consolidation projects. 

Learn more about Applaud’s EPACTL tools...




The Only Data Repository
In addition, Applaud is the only software with a data repository designed for data quality and data migration/consolidation projects.  Applaud's data repository is a dynamic data staging facility designed to support the high volume of data definition changes that occur in data quality projects - data is extracted only to find the content is not as expected.  Applaud's Data Repository dynamically responds "on-the-fly" to data definition changes. 

For example, suppose that during the development/testing phase a data field is initially extracted with the understanding it contains a character value.  Further, suppose it is subsequently learned that the actual data in the field is numeric (i.e., it contains numbers instead of ABC etc.).  With Applaud you simply change the data definition.  Applaud's Data Repository instantly responds, eliminating the need to re-extract the data.  The time saved is substantial, making development of Applaud solutions much faster than traditional RDBMS technology.  Again, Applaud is the only software with a data repository. 

Learn more about Applaud's Data Repository...

The diagram below illustrates the Applaud solution. 

The Applaud Solution
Integrated EPACTL Tools, Data Repository, Reusability, and RAD Design
Dramatically Speed Data Quality Projects

50% Reduction in Time and Cost
Applaud's integrated EPACTL tools, data repository, reusability, and rapid application development (RAD) design deliver a huge advantage over every other data quality alternative.   The net result is a conservative 50% reduction in the time and cost compared to every other alternative.

No other software provides the speed and flexibility of Applaud.  As a direct result, no other professional services organization can match Premier International's quality, speed and affordable cost. 

So how does the Applaud data cleansing solution work?  Every project is different.  That's where Applaud's flexibility and Rapid Application Development (RAD) tools play such an important role.  A summary of Applaud's primary features and typical project phases are provided below…

Plan – Identify Sources, Formats, and Known Issues
We begin the project by meeting with your “data experts” to identify the data sources that will be involved.  (The Data Expert is the person who knows the most about the data).  For each data source we will need all known information regarding the data format, content and structure, and any known data quality issues. 

The result of this phase is a comprehensive list of the sources of data to be included in the project, along with the identification of all known issues.  This will be used as the initial scope of the project, although in some projects the scope changes dynamically as facts are uncovered.

Extract - Load Data into Applaud's Data Repository
The first step is to use Applaud's powerful extract features to load source system data into Applaud's Data Repository.  RDBMS data sources are accessed through Applaud’s proprietary drivers.  Applaud’s unique “Visual Record Layout” feature makes it easy to define source system data, even complex data from poorly documented systems.

Profile - Analyze Data Content
In the next step we use Applaud's comprehensive profiling tools to identify data content issues.  Profiling provides detailed data statistics to guide the next steps of the project.  For character data, profiling identifies all distinct values (i.e., every code value) and their frequency distribution.  For numeric data, profiling displays statistics including the highest, lowest, average and total, as well as the number of positive values, negative values, zero/null values and any non-numeric values.  For dates, it identifies the highest and lowest dates and the number of blank/null values as well as any invalid date values. 

Profiling is a quick way to identify data failures such as missing data, invalid data and inconsistent data.  The results of profiling direct the next steps of the project. 

Analyze - Identify Data Structure Issues
Armed with the results of profiling, the project moves into the analysis phase.  Applaud’s suite of analysis tools include four styles of report generators and other advanced analysis features.  Applaud’s analysis tools can quickly identify data structure problems such as redundant data, orphans, failures in data relationship rules, invalid integrity constraints, parent/child issues, etc. 

The analysis tools also make is easy to "drill-down" into the data content problems found in profiling to further understand the issues.  For example, suppose that profiling identifies unexpected values in a code field.  Applaud's analysis tools can quickly identify the exact conditions where the unexpected values exist, and can easily provide detailed reports broken-down by each related business unit for subsequent analysis and resolution. 

Additional analysis tools include four types of random sampling tools to sample large volume data, the ability to parse unstructured data to identify component data, powerful features to identify duplicate/redundant data, and an extensive suite of tools for name and address cleansing.

Evaluate Results
Next, we meet with representatives from your staff to show the data quality issues we found and discuss the risk and alternatives for cleansing.  For example, if you are planning a migration to a new system, you might have alternatives to cleanse the data in the legacy system before the migration, cleanse the data as an integral part of the migration, or migrate the data and then cleanse the data in the new system.  Our experts will meet with your staff and discuss the pros and cons of each alternative.

Present Findings to Management
The Data Quality Audit project concludes with a presentation of the findings and recommendations to your management group.  We will identify any potential risk areas and will assist you in evaluating the alternatives.  The data quality findings are typically presented in three categories:

  • Low - Areas of negligible risk of quality problems
  • Moderate - Areas of moderate risk of data quality problems
  • High - Areas of significant risk of data quality problems

The presentation and our involvement in the assessment can be as detailed or as general as you want.  Remember, you are in charge of every phase of our work

What If the Audit Finds Problems?
If the Data Quality Audit project identifies data problems, often the next steps include a variety of cleansing activities.  When you use our Applaud professional services, the next steps are easy because the comprehensive solution is included in Applaud’s robust EPACTL tools.

Consolidate - Combine Related Data -Applaud's Rapid Application Development tools make it easy to combine selected data from matched records into a single record and eliminate duplicate/redundant data.  Data is extracted into Applaud's Data Repository for analysis and consolidation.  Staging tables are constructed where various elements of data may be quickly examined and consolidated.  Applaud speeds this process, providing a thorough analysis of the results for the client to examine.


Confirm - Manual Approval of Consolidation - These capabilities enable users to confirm (or reject) match candidates identified during the processing.  For example, Applaud can produce a spreadsheet (or spreadsheets) containing candidates for consolidation.  The client can then use the spreadsheet to specify which items are to be consolidated (or which should not be consolidated).  Applaud then processes the spreadsheet as specified.  Applaud facilitates client direction at any step in the process.


Transform - Correct Data Content/Structure -Invalid data values must be corrected and missing data must be calculated or otherwise provided.  This often involves complex transformation rules and additional data sources containing crosswalk/lookup tables to compute the values for selected data elements.  Third party data may easily be appended and applied at any step of the process.  Applaud makes this process easy with its strong transformation tools.  Applaud has the ability to quickly insert complex transformation logic and the ability to easily add any number of crosswalk/lookup tables to any component.


Certify - Standardize Name/Address Format -In addition, Applaud's comprehensive name/address cleansing offers the ability to determine if addresses actually exist, correct addresses to postal standards, and obtain CASS certification. Applaud includes the ability to compute Zip+4 codes, county names, geocode data (compute longitude and latitude) and other address-related information.

Capture - Manually Enter Additional Data - Further, Applaud includes the ability to quickly construct data entry screens (with comprehensive data validation) to capture changes for selected data.  These screens can be used as needed to capture data changes.  Data changes are then used to "override" appropriate data values at the "go live" date.

Manual Cleansing - Control Batches of Data for Cleansing - Applaud can also interface with Excel for manual cleansing projects.  Applaud can build “batches” of data in Excel spreadsheets for manual cleansing and can provide comprehensive validation upon re-importing the data after the cleansing.  Controls can be provided that report the status of each batch of data to ensure that every batch is correctly processed.  Ongoing features may be constructed that monitor subsequent changes during cleansing and report any issues that may cause problems.


Standardize - Format Data Consistently -All data must be formatted consistently according to system rules.   Applaud makes it easy to standardize the data to ensure a consistent format throughout all records.  For example, this might include the normalization of phone numbers, tax ID numbers, part numbers, product information, etc.  Every project has its unique challenges.  Applaud makes it easy to solve the most complex cleansing requirement.


Results Analysis - Ensure Cleansing is Complete - Applaud's four styles of report generators and advanced analytical tools are designed to be able to analyze the results of cleansing as well as the original data.  This makes it easy to ensure that all data issues are fully corrected and resolved.  Applaud analysis components may be run at every test date to confirm that the cleansing is successful, and identify any new issues.


Load - Load the Results of Cleansing to the Target System - When all of the data is cleansed, the results are loaded to the target system.  Applaud's powerful load features make this an easy process.  Data can be loaded to the original source system, or it can be loaded to a new system that is being implemented.


On-Going Data Cleansing -Applaud is also the ideal solution for ongoing data quality initiatives.  Applaud data cleansing processes can identify missing/invalid/inconsistent data, correct problems, cleanse addresses, identify duplicates, produce data quality metrics, and build many other data quality-related processes.  Everything developed in the initial migration project is reusable in ongoing data quality solutions, providing complete solutions quickly and at very low cost.  Applaud on-going cleansing processes may be run as needed using Applaud's robust batch scheduler.  (Hourly, daily, weekly, and monthly processes are supported.)  Alternatively, any other batch scheduler may run Applaud processes.





Reasonable Rates + No Software Cost
Our Applaud Professional Services Group looks forward to the opportunity to help with your Data Quality Audit project.  Our hourly rates are very reasonable and again, you should expect the time and cost to be at least a 50% lower than every other alternative.  And as an added bonus, there is no software cost for Applaud on your Data Quality Audit project.   Our data quality experts will provide Applaud at no cost to you.


Getting Started
Our Two-Week Pilot Project is designed to give you a no-risk way to see the Applaud solution at work in your environment.  We will work on-site at your direction on your live data cleansing project for two weeks.  If, at the end of two weeks, you are not absolutely amazed by our success, send us home and you will owe us nothing but our travel expenses. 

However, if you are impressed by our success (like every organization that has accepted this offer), we will bill you for the initial two weeks and we will continue to work at your direction to ensure the success of your project.

Contact us at 800-426-0428 or to get started.  You won't be disappointed…


"Wow . . . I'm convinced!"

Chief Architect
Global appliance manufacturer
on the second day of their Pilot project Details…


Featured Case Study

Supply Chain Data Quality Audit - A global manufacturing organization had implemented a new supply chain solution, only to find significant data quality problems.  Details…


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