Data Analytics EVOLUTION in a Life Sciences Organization
Transforming a Life Sciences Organization's
Data Analytics Hub from Cloudera Hadoop to AWS Redshift


Life Sciences
Like many life sciences organizations, one of our global clients was faced with justifying the value proposition of its Cloudera Hadoop stacks in Europe and the US.  As this organization continued to evolve in its data analytics journey, the management team recognized they exhausted their routine ingestion of unstructured data and that future demand could be addressed through other options.  Cloudera was becoming a very costly system to support, no thanks in part to Cloudera's 35% price increase following its merger with Hortonworks.  The need to reduce data warehouse expenses was becoming a critical concern.


Our consultant was instrumental in transforming the data analytics hub and developing the processes needed to migrate the data and support the environment.  He reported to upper management and was accountable for keeping the project on track.  He also led the implementation of critical tools and developed the processes needed to reduce operational support.
Our consultant transformed the environment by implementing AWS Redshift and integrating AWS Identity & Access Management (IAM). The solution implemented a unique workaround for SAS and R libraries that were written for Cloudera, reducing the need to rewrite queries.


Overall, the solution reduced data warehousing compute and labor support costs by 57%, saving the company hundreds of thousands of dollars annually.  Through our personal touch, we ensured our program sponsor was successful in his mission to deliver value to the business and implement innovative, highly-performant technology.
Our consultant led the way for the organization to transform additional data analytics environments at this client.
Key deliverables included:
  • 8 to 20 times improved query performance using AWS Redshift 
  • 57% reduced compute costs with AWS Redshift 
  • Best Practices guides to ensure success for data scientists and data analysts 
  • AWS Redshift Operations Manual and RACI matrix to ensure quality support
  • Single sign-on solution, via ADFS and AWS Identity and Access Management
  • Single data query tool for all users


Life Sciences


IT Strategy & Transformation
AWS Cloud
Data Analytics
Architecture & Technology

Designed to

  • Reduce data analytics  hub operating costs by 57%
  • Increase performance by 8 to 20 times for data scientists and data analysts
  • Deliver innovation technology and best practices