Establishing 'Making it Happen' as a 'Formal & Predictable' Discipline

Data Quality Overview	Customer Data Quality for Customer Relationship Management

Execution-MiH ENCYCLOPEDIA → Enterprise Intelligence → SECTION - Data Quality →

CHAPTER -

Data Quality Assurance and monitoring

Prevention is better than cure. Quality can be much assured by pro-active assurance controls, while designing your systems and processes. Avoid bad data through interface controls, data standards, data models, database & Data processing and business controls.

Topics

Data Interface Exchange Controls

One of the biggest issues of data quality in this ever increasing world of inter-connected systems. Data exchange across the system needs controls at a record, file, application and database level.

Data Entry Input Form Controls

A set of controls to ensure that users enter the correct data in a systems, leads to quality assurance at source.

Data Domain and Data Standards Controls

A set of controls to ensure that users enter the correct data in a systems, leads to quality assurance at source.

Data Model Entity Relationship Controls

Data Model imparts the business rules of cardinality, optional v/s mandatory, primary keys etc.. By ensuring system adherence to data model, the data will represent the real world.

Business Rules Definition

This control is nothing but asking for the systems to adhere to the business rules as defined. The problem is less to do with implementing business rules, but more with documenting them properly in the first place.

Batch-Processing controls

With tons of data getting processed in the night, a robust flow sequence and pre processing-wip-post processing batch processing controls are must.

Business Process Controls

Robust business processes ensure that data is properly managed before it is entered in the system and after it is produced from the system.

Business Partner Interface Controls

Just like a supply chain, the business partner's systems also need to be integrated in terms of standards and business rules..

Data Quality Monitoring

Data Quality constantly need to be expected, and the approach ranges from doing it real time to post facto. It is better to find an error, before customer or regulator finds it.