Business Impact

  • Designed and engineered the information flow

  • Provided high-impact future learning platforms

  • Identified and delivered appropriate data to the application at the right time

  • Enabled analytics team with advanced capabilities to adapt to rapidly-changing business needs

Customer Key Facts

  • Location : North America
  • Industry : Publishers

Problem Context

The customer, an American multinational publishing company, focuses on academic publishing and instruction materials. The Data Analytics & Insights team used Netezza Data Warehouse Appliances as analytical Data Stores hosted in their data center. IBM gradually discontinued support for non-production and production Netezza appliances.



  • The customer faced the challenge of combining the varied data formats (xml, json, text, etc.) from internal/external sources with other datasets
  • Data needed to be transformed and stored in the relational format before being used.
  • The customer also required scalability, reduction in storage and compute, and spinning up data science compute clusters dedicated to specific business units.



Migration of Data Assets from Teradata


  • Exported data from RDBMS to S3 buckets using python connectors
  • Imported data into staging tables from S3 buckets
  • Built CDC Logic to handle the Insert/Update/Delete in Snowflake


Successfully migrated critical data from legacy systems to Snowflake, transformed data to be analytics-ready and business-friendly

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