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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
Snowflake vs Azure Data Factory: Key Differences and How They Work Together
Snowflake is a fully managed, multi-cloud data warehouse built for high-performance analytics, while Azure Data Factory is a serverless integration
Microsoft Fabric vs Amazon Redshift: Key Differences and Which Fits Your Data Strategy in 2026
Microsoft Fabric is an all-in-one SaaS analytics platform combining data engineering, warehousing, real-time analytics, and Power BI over a unified
Snowflake vs Azure Synapse Analytics: Comparison and Strategic Evaluation in 2026
Snowflake is a multi-cloud SaaS platform built for independent scaling of storage and compute across AWS, Azure, and Google Cloud.
Cloud-Native Data Modernization Services Guide: What Enterprise Buyers Should Evaluate in 2026
Modernizing legacy on-premise data infrastructure into cloud-native architectures requires a phased approach: assessment and strategic roadmapping, secure data migration to
Hadoop to Databricks Migration: Modernizing Legacy Data Lakes
Migrating from Hadoop to Databricks transitions your data architecture from a legacy on-premises system to a cloud-native Lakehouse Platform. This
AI in BFSI: Use Cases for Banking, Financial Services and Insurance
Artificial intelligence in BFSI (Banking, Financial Services, and Insurance) transforms operations through real-time fraud detection, automated loan underwriting, personalized customer
Agentic AI in RCM: 6 Tasks AI Agents Are Handling Today
Agentic AI in revenue cycle management converts manual billing into autonomous, outcome-driven digital workflows. Core capabilities include autonomous decision-making for
Data Analytics in Modern Financial Services: Functions, Use Cases, AI Trends & Future
Data Analytics in Financial Services: Functions, AI Trends & Future Introduction Need for data analytics Functions Types Growth Strategy AI,
Agentic AI in Manufacturing: 6 Use Cases, OT/IT Architecture & Real Examples
Agentic AI in manufacturing deploys autonomous systems that perceive real-time shop floor signals, reason through operational objectives, and execute complex
Ecommerce Demand Forecasting: Methods, Models & Best Practices
Online retailers rely on demand forecasting to anticipate buying volume by analyzing historical sales, seasonal patterns, and real-time market signals.
