Organization: ZS Associates
ZS is a management consulting and technology firm focused on transforming global healthcare and beyond. We leverage our leading-edge analytics, plus the power of data, science, and products, to help our clients make more intelligent decisions, deliver innovative solutions and improve outcomes for all. Founded in 1983, ZS has more than 12,000 employees in 35 offices worldwide. To learn more, visit https://www.zs.com/.
Traditional customer engagement approaches, through various channels, have been product-centered and disjointed, leading to non-personal experiences. This reduces the impact of commercial actions and overall impressions, resulting in fewer patients accessing necessary therapies. To address this, adopting an Omnichannel approach with a customer-centric focus is essential.
ZS has successfully launched the “Client Engagement Transformation” for multiple brands, establishing it as the flagship commercial program for Digital Customer Engagement. ZS has partnered with the client to provide them with innovation, process improvements, and automation support.
To bolster operations, ZS has also implemented a development capability on the Dataiku platform, complementing the existing operations with a ‘Dev + Ops’ setup which is lead to the onboarding of over 200 models on the Dataiku production environment, with a dedicated team of 90+ FTEs, including Data Engineers, Data Scientists, and Cloud experts. Challenges related to ML Ops capabilities, Pipeline orchestration, code versioning, and flow visualization were effectively addressed through the central Dataiku platform.
Dataiku, a data science and machine learning platform, facilitates collaboration among analysts, data professionals, and scientists for various data projects. It offers a uniquely unified platform offering wide variety of data preparation, visualization, machine learning, and model deployment tools. Major challenges related to infra-computation for large-scale projects were addressed by transitioning from EMR to EKS clusters, optimizing Spark configurations, and enhancing Dataiku server performance.
Dataiku Upgrades and Optimization
Compute cluster change EMR to EKS on Dataiku:
Job Optimization For Increased Performance:
Disabling Spark Dynamics Allocation:
Dataiku Server Optimization for Better Performance:
“I really appreciate the proactiveness of our ZS team to not only identify the issue but also providing a clear explanation to our key stakeholders on WHY this happened. Our ZS team also fixed this issue in record time. Our key stakeholders acknowledge this effort and the good discipline the ZS team has developed in resolving such issues. Please extend this appreciation to our ZS team.”
(Director, Machine Learning and Data Engineering)
“It has been a great partnership so far and looking forward to continuing this partnership to drive further value for the ZS team. I am particularly impressed with the progress made by the team in terms of technical understanding as well as brand specific knowledge in less than 3 months. We are happy with the overall work of the team.”
(Manager, Advance Analytics)
“Regarding “Standardization of Current Output generation process.” This will eliminate the tail end of the pipeline which is most error prone (and very time consuming). Thank you everyone for the hard work investigating and agreeing on a final output.”
(Principal Data Scientist)
Business Area Enhanced: Marketing/Sales/Customer Relationship Management
Use Case Stage: In Production
Without Dataiku process :
With Dataiku Integration:
Value Range: Dozens of millions of $