Case Study

Enterprise Transformation for Consumer Electronics Manufacturer


Insights driven enterprise transformation for large US based consumer electronics manufacturer

The client

The client is a US based large high tech manufacturer that specializes in consumer electronics and one of the large online service providers.


The client was facing exponential increases in cost and reductions in performance across core business platforms due to scaling to meet business and market demand. This resulted in:

  • Exponential increase in data infrastructure costs: Data is doubling every year resulting in exponential increase in traditional data and DW infrastructure costs to meet the new demand.
  • Performance: Systems were experiencing longer load times than desired. Additionally, with increased demand to process unstructured data, they were doubling existing BI infrastructure YoY to maintain current response time.
  • Throughput: Transactions are generated at the rate of 4.7 million an hour resulting in 3.5GB of data velocity an hour.

Our solution

Infosys leveraged our SMART EA framework and the Infosys Big Data Edge platform (now known as the Infosys IIP Platform) to architect a scalable and fault tolerant future state. We re-used multiple data ingestion, data processing and semantic analysis modules and built a re-usable and holistic Hadoop based platform anticipating future growth across business units.

As a strategic vendor for big data and analytics, Infosys was responsible for architecture, data ingestion design, platform development & maintenance, production support and overall program governance for the future state platform.

Infosys was responsible for conceptualization, architecture definition, design and implementation of Augmented DW leveraging a combination of new Big Data technologies and traditional DW technologies to meet growing data demands, data velocity and heterogeneity of data. Examples include:

  • Utilizing Big Data technologies like Hadoop MapReduce, HDFS, Hive, PIG frameworks to augment the current enterprise data warehouse
  • Leveraging Informatica for extracts from source systems and loads and supplement with BI and reporting features supported by traditional technologies like Teradata


Infosys drove a successful insights driven enterprise transformation leveraging our strategic and technical expertise. As a result, client achieved the following:

  • Scalable and fault tolerant distributed file system using HDFS resulting in overall annual operational cost reduction from 300M to 80M
  • Reduced total cost of ownership across application landscape by approximately 33% with approximately 50% reduction in mainframe applications by 2019
  • Highly scalable processing engine, Hadoop MapReduce resulting in reduction in data Load times from 2 hours to 10 minutes
  • Data processing times reduced from 4 to 2 hours

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