X4DB data quality framework
"Nearly 80 percent of British companies say that their legacy tech systems are hampering IT/business alignment and possibly damaging business executives' impression of IT."
ITBE

Data Quality Process

IT Dimensions offers a robust data auditing, cleaning and reporting services. We assist our customers in standardizing data across their heterogeneous systems.

Typical Data Cleansing Process:

Data Profiling

By understanding the data and identifying data problems before starting a data-extensive processing project, we can drastically reduce the risk of project cost or failure. We evaluate the existing data, check for inconsistencies or anomalies to identify problem areas and data accuracy level. The results are presented to the client in a form of a report on data patterns, most common errors and frequency of occurrence. We can deliver the initial analysis in less than one week on a selected sample of data.

Data Classification

To make a better targeted business decision, data is often categorized based on various rules such as industry codes, department rules or other compliance requirements. This process is often not clear-cut. Part of the process is a pattern discovery and business rules enhancements. Our classification process ensures the best possible results by providing good iteration cleansing process, name based classification and utilizing AI algorithms. In the next phase, our team along with your staff will redefine data references, design customized rule sets and assemble the data cleanup process.

Data Cleaning

The data cleaning process begins with customizing existing algorithms according to patterns and business rules from previous steps. Additionally, to ensure the project success, we need to understand how the clean data is distributed and utilized within your organization. Primarily, how the data supports business objectives. The results of the cleansing process are pushed to presentation or matching layer for additional approval.

Approval Reporting

Approval Reporting solves two purposes:
  • 1. Refining patterns and rules for different business units
  • 2. Approval process before data are fed to reference / target system

Our powerful data presentation framework allows us to assemble web-based approval process for additional pattern refinements and design interfaces for the end-user to view data and approve changes. For convenience, data are exported to spreadsheet programs for additional pattern discovery if needed.

Reconciliation Reporting

Internal changes due to Mergers & Acquisition activities, new FCC rules and other business activities cause business rules to change rapidly. The existing data-warehouses and data marts often don't provide reports that allow for enough flexibility for these fast-paced business rules. Our powerful data presentation framework allows us to assemble very flexible web-based reporting from existing templates and design interfaces for the end-user to view data and approve changes. Our extensive data-architecture experience helps us to support reporting with dynamic low-cost data stores.

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Data Quality