Data Analytics for Data Profiling, Data Quality, and Archival assessments


Client Overview

Leading Canadian telecom company and they leveraging the power of world-class wireless and fiber networks. They deliver a wide range of service innovations to consumers, businesses, and government customers across Canada.

Key Facts: 

  • Founded in 1880. 
  • Operates in Canada. 
  • Providing service for Home and Commercial purposes for Fixed-line and mobile telephony, LTE Advanced, Fiber Internet and TV, Wireless Home Internet, cloud and data hosting, IP voice and collaboration, Connected Cars, Smart Cities and Internet of Things.

Project Scope

  • Assessment of health and quality of master data in SAP ECC to determine data readiness for SAP S/4 HANA
  • Assessment of SAP ECC, SAP BW, and Hybris recommendations on archiving and migration to HANA database

Business Situation

Customer using SAP application for more than two decades and they want to assess the master data and planned to keep the transaction records for 7-10 years as per the Canadian government norms before migrating to SAP S/4 HANA and HANA database.

Technical Situation

SAP applications have transaction-intensive, critical high-volume ERP data, collecting and storing huge amounts of data resulting in an exponential increase in the size of the database and it is high-priced when we migrate the whole amount of data to S/4 HANA. 

The customer planned to remove archive and purge on the obsolete data from SAP Systems and before removing the data it is planned to analyze the data in terms of Health, Quality, and Volume of the data.


The solution proposed was dataZense (a cloud-based Data Analytic solution) that runs on the ChainSys Smart Data Platform. dataZense is used for bigger volume of data analytics, user friendly dashboard and reconciliations dashboard during migrations This also enables the usage of Agile methodology wherein the business users can participate in the validation of the results very quickly. dataZense is based on Web-service based architecture and is fully configurable to suit the business needs. 

  • Data Profiling algorithms analytics like column profiling, table profiling, relation by data, etc., 
  • Identifies intended & unintended duplicates using automated match algorithms with analytics dashboard to see the duplications like – Matched, Unmatched, Survivor and Victim. 
  • Data dependencies dashboard and analytics
  • Data readiness dashboard and analytics



The implementation of dataZense was done in an agile manner with the first round of testing extended to 8 Weeks. Agile execution is enabled by using templates, configurable, and non-programming approach to the solution process. With a minimal footprint and virtual team operation, all the activities are fully automated.

Below are some Key Benefits.

  • Provided Data Quality issues 
  • Downstream Data dependency matrix provided for master data
  • Potential duplications 
  • Data Archiving recommendation 
  • Data Governance recommendation 
  • Migration data readiness for S/4 HANA.

Products and Services Used

dataZense - To Visualize, Analyze, Catalog and Scramble Data for Effective Decision Making & Security.


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