Database Consolidation

Case Study Data and Analytics

A solar innovation corporation utilizes our Data and Analytics solution to consolidate disparate data and empower their teams.  

SITUATION  

A leading global solar innovation firm experienced gaps in reporting and analytics capabilities. Their system consisted of five international databases that allowed for data storage but lacked the ability to be leveraged for data queries. The separate databases prevented information sharing between applications. Key issues to be addressed included: 

  • Data Quality  
  • Data governance and process controls  
  • Manual reporting process  

SOLUTION 

As a leading Big Data services provider, we designed and implemented a Hadoop data lake consolidating the unconnected data from the five databases. The data lake was built on Amazon Web Services as a scalable and centralized solution. The solution, coupled with our process improvements, leveraged their deep data science expertise and resolved the previous issues. The solution provided an automated predictive model with a self-service yield calculation reporting solution.  

Implemented hadoop data lake 

RESULT  

Our solution ultimately provided the following values to the client:  

  • Automated data integration empowering reporting users with self-service  
  • A scalable solution allowing applications to share information, preventing silos  
  • The predictive model created actionable insights  
  • Accurate yield calculation without quality concerns