Gartner Expert

Sharat Menon

Sr Principal Analyst

Sharat Menon is a Senior Principal Analyst in the Tech Product Manager team of Gartner's Technology and Service Provider (TSP) organization. He currently covers the data integration software market and the database management systems market. Furthermore, Mr. Menon tracks the emerging trends in data management, such as data fabric architectures, DataOps best practices, citizen data management and augmented data management, and how vendors can leverage these trends for sustainable growth.

Previous experience

During his stint at EXL, Mr. Menon worked on managing the clients' corporate travel data flow across systems, right from data ingestion, data scrubbing, data integration, analytics and reporting, for creating standardized and ad hoc dashboards to measure the performance of the contracts that clients have in place with airlines, and hence assist them in negotiating better deals, based on trends and patterns in the data as well as competitors' benchmarks.

Professional background

Infosys

Systems Engineer

Infosys

Associate Consultant

EXL Service

Lead Assistant Manager

Areas of coverage

Product Planning

Product Development

Product Introduction

Messaging and Differentiation

Technology Market Essentials

Education

Post Graduate Diploma, Management in Information Technology, Institute of Management Technology

Bachelor in Information Technology, Mahatma Gandhi University

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Top Issues That I Help Clients Address

1Go-to-market planning for data integration & DBMS vendors: Positioning and messaging, understanding the competitive landscape

2Trends in data delivery styles: Bulk/Batch DI (ETL) vs. data virtualization vs. data replication & synchronization vs. message-oriented movement vs. event streams

3Trends in deployment strategies for data management tools: On-premises vs. cloud vs. hybrid vs. multicloud vs. intercloud

4Data preparation for business teams: How to penetrate the market and sustain growth

5Emerging trends in data management - data catalogs, data lakes, data fabric, DataOps