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Data-lake and Dashboards for business requirements| AspireNXT

Executive Summary

Our client has been a pioneering onboarding and engagement network for cloud workforces. They also wanted to seamlessly transform and analyze this data to gain actionable insights into the attainment of performance goals through surveys and quiz.

About the Customer

Our client provides an onboarding and employee engagement experience tailored to organizations which are designed to be informative and interactive. They aim to increase new hire experience while also building a foundation for employee success by getting them up to speed on new procedures and providing a dependable source of reliable company information.

Customer Challenge

Customer’s use case was to create insightful dashboards on a Managed Services platform which used embedded analytics in the HR portal for their clients which should be able to track critical management program and surveys by enabling them to move from static spreadsheets email reports and ad-hoc analysis to always-available dashboards.

Serverless Challenge

A serverless architecture is a way to build and run applications and services without having to manage infrastructure. The Customer no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Since, the size of the data is not defined and the data will be growing in future, the serverless architecture from AWS services has been chooses. For the data migration, AWS database migration services(DMS) is used, for storage Amazon Simple Storage Service(S3) is used. For the data transformation and data cleaning AWS Glue has been used and for building data marts AWS Athena has been used.

Partner Challenge

  • In the subsequent sequence, the overall data flow from extraction in SQL to the final dashboard is carried out.
  • AWS Database Migration Service is used to migrate the RDS source(MySQL database) to transfer full data load and then delta data only.
  • For data engineering, AWS Glue was set up, and data quality checkpoints were performed on the data lake using AWS Lambda.
  • For all the data that passed the data quality check, a separate database was created, Athena was configured to query the data and ingest the data to QuickSight.
  • The data validation and transformation were done, and visualization were created as per the client requirements ,and then these dashboards were embedded in the client domain.

AWS Services Used

As part of the solution architecture, the following AWS Services were used in the development of the QuickSight dashboard embedding project:

  1. AWS DMS
  2. AWS Glue
  3. AWS S3
  4. AWS Lambda
  5. AWS Athena

AWS QuickSight

 

Third-party applications or solutions used.

Architecture Diagram, MySQL Workbench

Results and Benefits

  • A high-level view of aggregated survey & quiz responses from employees across different surveys to recognize and analyze the perception for the surveys answered.
  • The HR interaction with the portal is improved, encouraging the customer to make a thoughtful decision.
  • Open-ended responses were able to analyze as a Word Cloud.
  • Client engagement in collecting benchmark results which leads to increase employee efficiency is increased by 50%.
  • With excellent enterprise-grade dashboards, visibility and control over data have increased by 30%.
  • The outcome was to get reliable data from the target audience, create and publish the dashboard on the client web portal utilizing web embedding
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