How ALLEN Digital Built an Analytics-Ready Stack in 3 Days with Hevo Data

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About ALLEN Digital

ALLEN Career Institute began in 1988 in Rajasthan, India and is widely known for helping students prepare for competitive exams such as JEE and NEET. Over time it expanded to many centers and online programs. During COVID, the company launched ALLEN Digital, which grew so quickly that if viewed as a separate “center”, it now ranks among ALLEN’s top five. The early technology stack, however, was designed to run the product rather than support analysis. “There was no way we could generate any insights out of the current setup,” recalls Madhur Gadiya, Director of Analytics at ALLEN Digital. The team therefore created a separate analytics environment on Amazon Redshift and set out to move data into it quickly and reliably without investing months in custom pipelines.

What do they do What do they do?
ALLEN Digital provides online and hybrid learning for competitive exam preparation.
Industry Industry
Education
Location Location
Rajasthan, India

The Challenge: Data integrity, centralization, and freshness

The team required analytics and production to remain separate to protect performance and reliability. At the same time, the data needed for insights lived across many systems. Core operations ran on MySQL, MongoDB, and DynamoDB, while growth and engagement data came from Facebook, Google, CleverTap, AppsFlyer, YouTube Analytics, Google Sheets, and both internal and third-party surveys. They needed a way to centralize data with the right cadence and clear operational visibility. They looked for a tool that could connect sources to Redshift quickly, meet SLAs for accuracy and timeliness, and provide alerts over email and Slack. They also needed to meet security and DevOps requirements, and a pricing model that allowed them to control costs.

The Solution: Quick, hands-free, and reliable

With production and analytics separated, ALLEN Digital selected Hevo Data as the first tool in the analytics stack, recommended by team members who had prior experience with the platform. The results were immediate, with setup taking only three days. Onboarding third-party sources was similarly fast, with most integrations configured in just 30–40 minutes.

“We were able to get everything set up in about three days. Zero maintenance, very high accuracy. Most of the things that you could think about were handled out of the box.”


ALLEN Digital's Data Stack

Hevo’s plug-and-play pipelines with automated schema mapping absorbed common source changes such as fields being added or removed so the team did not need to spend time on constant fixes. Built-in monitoring and alerting prevented silent failures, and a dedicated Slack channel kept everyone informed. In addition, event-based pricing matched ALLEN Digital’s predictable volumes, keeping costs transparent.

As the platform matured, analytics became a shared capability rather than a point solution. Clean, organized data in Redshift now serves analytics, data science, operations, marketing, and sales, visualized in AWS QuickSight and a self-hosted Apache Superset.

The Outcome: Quicker insights, leaner operations, better decisions

Time to value accelerated dramatically: with accurate loads, proactive alerts, and configurable refresh schedules, decisions moved faster. Near-hourly signals from free users, for example, help marketing act promptly on abandoned-cart scenarios.

Engineering effort also dropped. At peak, the team ran around 80 pipelines; and operate 20–25 on average consistently. Across initial setup and ongoing maintenance, they saved 20–25 person-months in engineering effort. Pricing being tied to events kept spending predictable, and when external APIs such as Salesforce or Facebook Ads changed, Hevo’s support provided clear timelines for updates.

“Hevo just blended in quite seamlessly, and we could get to the analysis part really quickly, rather than spending two to three months on setting up the entire infrastructure.”

With Hevo as the first layer of its analytics stack, ALLEN Digital now runs centralized, reliable, low-maintenance pipelines into Redshift, delivering faster insights with predictable effort and cost. Looking ahead, the team plans to deepen this shared analytics foundation so product, operations, marketing, and student-success teams can make even more timely, data-driven decisions.

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