Unlocking $3 Million in Cost Savings with Innovative Data Lake Solutions

A global communications provider saved $3 million by migrating from expensive legacy systems to a Cloudera Hadoop data lake, turning an aggressive data lake solutions project launch into a multi-year managed services partnership.

At a glance

Success Highlights

Challenge

This global provider of communication and network infrastructure services helps clients communicate more efficiently and connect with their audiences through a diverse portfolio of solutions—from unified communications and safety services to interactive automated notifications, telecom services, and specialty agent support.

Facing a critical inflection point in its data management strategy, the client needed to modernize its infrastructure by implementing big data lake solutions as its standard data warehouse repository, replacing costly legacy systems that had become inefficient and expensive to maintain.

The stakes were high—a projected $3 million—requiring experienced Hadoop engineers and admins to help set up the new environment while retiring Splunk and sunsetting other legacy applications.

Unlocking $3 Million in Cost Savings with Innovative Data Lake Solutions

Solution

The partnership began through a Cloudera recommendation, but it was Concentrix’s approach that sealed the relationship. Even before the official partnership commenced, the Concentrix team demonstrated their commitment through comprehensive proof of concept work and technology discussions.

Concentrix’s Data & Analytics team took a methodical, education-first approach that addressed both immediate technical needs and long-term knowledge transfer:

  • Provided multiple options for each PoC with clear recommendations based on budget, timeline, and available technology.
  • Delivered hands-on workshops and demos to educate the client’s engineers and business analysts on new tools and technology.
  • Brought the internal team up to speed quickly, enabling them to support ongoing operations.

The technical implementation was comprehensive, beginning with a use-case-driven roadmap that reflected the client’s actual business needs and priorities, allowing us to focus on delivering maximum impact:

  • Architected and deployed multiple clusters to build an integrated data repository accommodating larger strategic use cases across the organization.
  • Built data pipelines and migrated content from traditional relational data houses into Hadoop.
  • Set up an operations team to monitor pipelines, follow up on failures, and propose modifications.
  • Migrated content from several business intelligence tools to Tableau.

For the pilot project, we focused on interactive services—a business unit representing more than 13% of the client’s revenue:

  • Completed proof of concept within six weeks using Cloudera Hadoop CDH 5.
  • Ingested raw IVR logs into HDFS, partitioned by day.
  • Analyzed data using Impala with Tableau for visualization.

The scope extended beyond the initial implementation to include operational management and maintenance of multiple clusters, encompassing administration, monitoring, and DevOps—ensuring the platform would continue performing optimally long after launch.

“The Concentrix team was the most helpful with its proof of concept (PoC) and technology discussions. They provided support and consulting even before our official partnership started.” –Client Software Engineer

Outcomes

The financial impact was substantial. Through impeccable execution of a robust architecture and disciplined data governance policies, Concentrix helped the client corporation save nearly $3 million by decommissioning expensive legacy systems and consolidating their data infrastructure.

Beyond the immediate cost savings, the implementation delivered lasting operational and analytic insights that continue to drive business value. The success of the project cemented Concentrix as a strategic partner, leading to a multi-year managed services contract that ensures ongoing optimization and support.

The transformation demonstrated that a successful Hadoop data lake solutions implementation requires more than technical expertise, demands a partner who can educate, collaborate, and deliver results under pressure while building internal capability for long-term success.

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