Introduction
Data Lake Platform Evaluation for Enterprise Analytics enables organizations to select the right data foundation before scaling analytics initiatives across the enterprise. As companies adopt advanced analytics and AI-driven insights, choosing the appropriate data lake platform becomes critical for ensuring performance, scalability, and usability. However, evaluating competing technologies often requires practical validation beyond theoretical comparisons.
This case study highlights how a travel technology firm conducted a structured data lake platform evaluation to determine the most suitable architecture for enterprise analytics. Through a hands-on pilot comparing Cloudera Altus and Azure Databricks, the organization tested platform performance, scalability, and usability while implementing real HR analytics use cases. As a result, the firm gained clear insights into platform capabilities and established a strong foundation for future analytics expansion.
Customer
The customer is a travel technology firm focused on building advanced analytics capabilities to support operational and strategic decision-making. As part of its data transformation initiative, the organization explored next-generation data lake platforms that could support enterprise-scale analytics workloads.
To validate the right technology choice, the firm decided to run a structured pilot focused on HR analytics use cases. This approach allowed the organization to assess platform capabilities in real-world scenarios while minimizing long-term implementation risks.
Business Objective
The primary objective was to identify the most suitable data lake platform for supporting enterprise analytics initiatives.
The organization aimed to compare Cloudera Altus and Azure Databricks through a hands-on pilot that evaluated scalability, performance, and usability. In addition, the firm wanted to demonstrate business value through HR analytics use cases.
Another important goal was to establish a flexible analytics foundation that could support future data-driven initiatives across additional business domains.
Scope of Services
The engagement focused on structured platform evaluation and analytics enablement, including:
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Design and execution of a pilot to evaluate next-generation data lake platforms
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Comparative assessment of Cloudera Altus and Azure Databricks capabilities
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Implementation of HR analytics use cases on shortlisted platforms
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Deployment and testing across AWS and Microsoft Azure environments
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Validation of analytics performance, usability, and extensibility
Benefits
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Clear visibility into strengths and trade-offs of competing data lake platforms
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Reduced risk in long-term technology platform selection
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Faster validation of analytics capabilities through real use cases
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HR teams enabled with actionable workforce insights
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Strong foundation for scaling enterprise analytics initiatives
Impact
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Confident selection of the most suitable data lake platform
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Accelerated readiness for enterprise analytics rollout
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Improved decision-making through HR data and workforce insights
