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LatentView Analytics
LatentView Analytics has been helping enterprises make smarter, data-driven decisions for 20+ years. Founded in 2006 by Venkat Viswanathan and Pramad Jandhyala, the company has grown into one of the world’s leading digital analytics firms — and became the first analytics company in India to go public in 2021.
LatentView brings deep expertise in end-to-end data engineering, business analytics, GenAI, and predictive modeling to 50+ Fortune 500 clients across tech, retail, financial services, and CPG. The company’s work spans everything from AI-powered sales forecasting and customer lifetime value modeling to large-scale data platform builds and GenAI implementation.
A publicly traded company serving the US, India, Canada, Europe, and Singapore, LatentView has been recognized in Forrester’s Customer Analytics Service Providers Landscape and among India’s Best Workplaces for Millennials. In 2024, the company expanded its capabilities through the acquisition of Decision Point Analytics, adding Revenue Growth Management and GenAI product solutions to its portfolio.
LatentView’s insights are shaped by real client engagements across industries — from building ML frameworks for telecom network reliability to developing guest lifetime value models for leading cruise lines. The perspectives shared on this blog draw from that hands-on experience working at the intersection of data, AI, and business strategy.
Learn more at latentview.com.
Blogs
Marketing Mix Modeling In the CPG Industry: Complete Guide For 2026
For CPG commercial leaders who fund media and trade from separate budgets and get asked to defend both. This covers
Marketing Mix Modeling In the Retail Industry: Enterprise Guide For 2026
For retail marketing and analytics leaders who own media budget and, increasingly, a retail media network. This covers what a
Data Catalog vs Data Lineage: Key Differences, Use Cases and How They Work Together
This guide helps CDOs, data engineers, data architects, and governance leads understand what separates a data catalog from data lineage,
Data Catalog vs Master Data Management: Key Differences, Use Cases and How to Choose
This guide helps CDOs, data architects, and data governance leaders understand what separates a data catalog from master data management,
Data Governance vs Data Management: Key Differences and How They Work Together
This guide helps CDOs, data leaders, and enterprise technology teams understand what separates data governance from data management, how the
Snowflake vs Palantir: Key Differences and Which Fits Your Organization in 2026
This guide helps CDOs, data architects, and enterprise technology leaders understand what Snowflake and Palantir each do, how they differ
Choosing Between Data Factory in Microsoft Fabric and Azure Data Factory in 2026
Data Factory in Microsoft Fabric is the SaaS-based next generation of Azure Data Factory (ADF), designed to unify data integration
Moravec’s Paradox and Whether AI Can Replace Humans
History shows predictions of technological advancements that put the future on a high pedestal.
Marketing Analytics for Financial Services: Use Cases, Metrics & Challenges
Marketing analytics for financial services connects marketing investments directly to customer acquisition, retention, and lifetime value while navigating compliance rules.
Lookalike Modeling: Examples, Types & Enterprise Strategy
Lookalike modeling is a machine learning technique in marketing that finds new prospects who share behavioral, demographic, or transactional traits
