Data at Scale: Crafting highly scalable and performant Modern Data Platforms

By Sameer Paradkar

Elevator Pitch

Designing modern data platform leveraging a variety of SaaS/PaaS services, within distinct layers consisting of load, store, process, serve, and consume. This platform facilitates decision-making process based on analytical, transactional and raw data; and enables extracting significant insights.

Description

Modern Data Platforms provides a proven pathway to optimizing how organizations store, structure, secure and perform analytics on their data. It enables businesses to build and sustain a world-class analytics infrastructure — migrating huge volumes of data, streamlining and structuring it, and providing a set of versatile, pre-built applications that give a range of users the ability to analyze data for their unique needs.

Modern Data platform enables: - Stakeholders to take evidence-based decisions based on analytical, transactional and raw data and extract value from data; - Data Scientist and analyst to consume and extract value from platform data. Enable data scientists to collaborate and use predictive and prescriptive analytics pipelines identifying metadata, insights and patterns in structured and unstructured data using analytics engines for big data processing; - Expose the outcomes of these pipelines as human and machine interfaces (Web UIs and services) and enable end-users and systems to search and consume the outcomes of data analytics activities. - Making use of advanced analytics such as text mining, NLP and AI to past and future unstructured information to augment it with metadata that lends itself to data-driven interrogation; - Implement and enforce data governance policies and processes

The talk is about designing Modern Data Platform leveraging a variety of SaaS/PaaS services, within distinct layers consisting of: load, store, process, serve, and consume and these various components via standard APIs.