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
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