Gartner Expert

Sumit Pal

Sr Director Analyst

Sumit Pal is a Research Director in the Data and Analytics Strategies group on the Gartner for Technical Professionals team. Mr, Pal provides guidance on big data architecture, data lakes, NoSQL databases and SQL engines for big data low-latency applications and data warehouses.

Roles and responsibility

Advanced Analytics, Data Architect, Solution Architect, Enterprise Architect, CIO, IT Director, Developers, Analyst

Previous experience

Prior to Gartner, Mr. Pal was an Independent Consultant working with multiple clients, both enterprise and startup in healthcare, energy and consulting sector developing big data applications and solutioning big data architectures for modern data platforms for batch and streaming workloads. He also worked on building ML and AI applications powered by large-scale distributed processing systems like Spark with Scala and Python & Keras.

Big Data Technology

Big Data Solution Architecture and Implementations

Hadoop, HDFS, NoSQL, Spark, Java, Scala, Python, R, Machine Learning, Data Science, Algorithms

Strategy Consulting, Building Modern Data Platforms and Recommending Architectures and solutions.

Mr. Pal has authored a book with Apress - "SQL on Big Data - Technology, Architecture and Innovations" and developed a MOOC - Big Data Analyst with Experfy.

Professional background

Independent Consultant Big Data, ML, AI

Independent Consultant Big Data, ML, AI


Associate Director of Big Data

LeapFrogRX (Acquired by ModelN)

Technical Director / Chief Architect

Areas of coverage

Data and Analytics Leaders

Data Management Solutions

Modernizing Application Architecture and Infrastructure (retired)

Analytics, BI and Data Science Solutions

Internet of Things (retired)


M.S., Computer Science, Asian Institute Of Technology, Bangkok, Thailand

B.E., Computer Science, Bengal Engineering College, West Bengal, India

Read More Read Less

Top Issues That I Help Clients Address

1Big Data Technology Implementations

2Develop Strategy for adopting Modern Data Architectures and Platforms

3NoSQL Database selection and modeling

4SQL Engines on Big Data Selections and Implementations for Data Mart

5Implement ML and AI Algorithms at Scale with Distributed Processing Systems