Session Outline

Organizations struggle to balance between avoiding the bottleneck of centralized, tightly-governed data warehousess and suffering from poor data quality and discoverability issues. The solution to this problem is Data Mesh where data as a product much like a app in AppStore or PlayStore. Data should be treated similar to various app in App Store or PlayStore that are discoverable, self-describing and usable i.e., people know where to find/search for the data, whether it is secure, trustworthy, whether it is interoperable, what it is and how to derive value from it etc. The data mesh offers many benefits such as it improves accessibility, empowers teams to own, manage and exploit insights from data leading to improved business agility and reduced business/process cost.

Key Takeaways

  • What is and is not a Data Mesh?
  • What are the benefits to the business?
  • How to design a Data Mesh? Available tech stacks.
  • When is a company ready to adopt Data Mesh strategy? What are the challenges?
  • A cases studies/example of success of adopting Data Mesh



Meenakshisundaram Palaniappan – Sr. Data Scientist | Danone Nutricia Research | Singapore

Sr. Data Scientist with 8+ years of hands-on experience in leveraging disparate data assets through advanced analytics. Helping organization develop data driven products/culture via effective data strategy advisory. Successfully managed several data science initiatives by collaborating with technical and business/clinical stakeholders, developing ML-AI models in areas of healthcare, sales and marketing, FMCG etc.

January 12 @ 13:00
13:00 — 13:30 (30′)

Stage 3

Meenakshisundaram Palaniappan – Sr. Data Scientist | Danone Nutricia Research | Singapore