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Minimize Operations Cost with Cloud Migration

Minimized data storage cost and data processing time

Challenges

  • The client is in search of a solution to reduce the operations costs involved in the data storage
  • SAS Database is used to store all client data. The amount of data is huge, and it is increasing at a faster rate. SAS licensing cost is high for each GB of data stored.
  • Processing time for mathematical operations is slower compared to a distributed system
  • Process the unstructured dataset and convert into structured ones

Solutions

  • Implemented an open-source framework to store and process big data using unique programming models – Hadoop distribution (HDP2.4)
  • Migrated to Hadoop ecosystem to enhance the performance of queries at a faster rate
  • Facilitated business logic upfront by creating data-lake
  • Executed the ETL process for extracting the data out of the source systems and placing it into the data warehouse

Tools & Technologies

Hadoop, SAS, Microsoft Active Directory, Apache Ambari, oozie

Key benefits

  • Increased the scalability by automating the fault-tolerance production
  • Excelled at high- volume batch processing. Cheaper hardware cost, faster performance, reliability of data
  • Pull pre-aggregated datasets to SAS database for faster querying