Business Situation

Data quality is the measurement of data based on quality factors such as accuracy, completeness, consistency and reliability. It has a high impact on transforming data into information, which is fundamental for business routines such as operational processes, system transitions, and reporting in organizations.

Our client, was suffering from data quality issues caused by having multiple data sources and structural differences like any other Telecommunications organization. For this reason, the accuracy and continuity of data quality processes in data management is very important.

Our Approach & Solution

Reducing data quality issues and raising awareness in source systems and business units are the initial steps for preventing duplications and anomalies. These steps start with data profiling. It provides an overview of the data and makes it easier to identify the points that should be focused on while creating data quality rules.

Non-qualified data and anomalies are detected with data quality rule sets determined by data stewards and technical teams. For our client, we built a workflow which examines data quality issues and addresses them to related departments or sources. Our work led the leading GSM service provider to prioritize problems, create backlog, manage demands and have a visible data governance structure. Data accuracy was improved day by day thanks to our rule sets and the company adapted a new perspective on data governance mentality.

Technologies

• Database procedures for data profiling and data quality rule check models.
• ICC Data Quality Tool for scheduling, monitoring and reporting non-qualified data.