Mindtree and AWS' Big Data Journey
“Sense-and-Respond” systems enable enterprises to be adaptive with data and insights. This is crucial to build responsive and personalized experiences. It enables enterprises to shift operational strategies based on these insights, or to make optimized decisions based on predictive analytics.
Engineering these systems on Amazon Web Services (AWS) is a more evolutionary architectural choice and a better economic imperative as storage and compute are separated, allowing for independent evolution and choices.
At Mindtree, we have deep experience across the lifecycle—from designing data lakes based on S3 to complex Customer 360 and predictive engagements on AWS. Some examples of our work are
- Enabled high performance predictive analytics for a leading CPG major to improve on-shelf availability and growth in assortment planning. Mindtree built a solution based on machine learning and advanced predictive analytics to improve their KPIs. We re-platformed and re-designed a comprehensive solution stack with data lake to seamlessly stitch traditional data sources with new age data for newer insights. The architecture uses AWS services like Amazon Redshift, EMR, and Spark with machine learning capabilities.
- Enabled a leading business school to gain better insights for the online program with advanced visualization techniques; they lacked an enterprise reporting tool to cater to their business needs. Mindtree built a unified data warehouse with datamarts and a common query/reporting layer based on MongoDB with Redshift to enhance data and perform efficient analytics. This solution provided insights towards new information like current trends and forecasts from ongoing participant admissions data. This in turn helped marketing teams plan more focused and aggressive social media campaigns.
- Improved revenue projection capabilities for a leading low cost airline through reduction in revenue projection analytics derived from booking and inventory systems. We reduced the the time taken to drive insights (average flight revenue, yield etc.) from 24 hours to less than 10 minutes. This solution made use of EMR, Pig and Hive for ETL transformation with Redshift as the analytics engine.
Mindtree is continuously evolving and has been largely successful in adopting AWS big data services. Our clients are excited with our recommendations on AWS big data managed services offering like AWS Glue ETL, AWS Glue Data Catalog, AWS Athena (Presto compliant), AWS ElasticSearch and AWS QuickSight.
Do get in touch with us for all your big data needs.