Gartner Expert

Ankush Jain

Sr Principal Analyst

Ankush Jain is a Senior Research Analyst at Gartner, primarily focusing on Data Quality and Data Management areas, where his key tasks encompass working on high-quality, actionable and consumable written research for IT leaders as well as providing actionable advise to IT Leaders/CxOs. Mr. Jain is responsible for conducting and driving critical research projects, including branded research comprising Magic Quadrants, Critical Capabilities, Market Guides, Toolkits, Best Practices and Survey Analysis.

Previous experience

Prior to joining Gartner, Mr. Jain was with American Express as Assistant Manager, Data Quality and Governance. His work at American Express involved driving key data governance initiatives, stakeholder management, supporting business analytics framework for MIS reporting, and helping clients with data quality issues.

Before joining American Express, he has worked with Pitney Bowes on its Spectrum Technology Platform as an Analyst, where he was a core member of the agile product development team that was entrusted with building and maintaining the Data Quality Products and dealing with clients like Twitter, Dropbox and Facebook. As a domain specialist, his role involved keeping a close eye on multiple other products in the market as well as keeping the management group well informed about the developments in the areas of big data and advanced data quality capabilities. He has also worked as an Informatica Developer with Accenture on two key projects with Morgan Stanley and AT&T, allowing him to traverse the complete data warehousing life cycle.

Professional background

American Express

Assistant Manager - Data Quality & Governance

Pitney Bowes Software

Analyst (Spectrum Technology Platform for DQ/DI/DG and LI)

Accenture

Informatica Developer

Areas of coverage

Data Management Solutions

Data and Analytics Strategies

Education

Bachelor of Technology, Electronics and Electrical Engineering

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Top Issues That I Help Clients Address

1Data quality (best practices, organizational structure, roles, tools)

2Data quality vendor selection / RFI

3Develop business case for data quality

4Data Management Software Contract Reviews