Case Studies

Telecom Client

End-to-End Automated ETL Solution

Data were sitting in silos throughout the client's data centres — no way to retrieve relevant insights. Sipher was tasked to centralize all data, better capture, organize, and structure the data in order to provide business intelligence.

What to do with all the data?

Terabytes of data were sitting in silos with no way of accurately obtaining business intelligence. It was essential for a large telecom company like our client to widen the accessibility of the data and provide accurate data analytics to each of their teams so they can accurately develop and finetune operational processes and marketing initiatives.

There were three major challenges:

  • Centralize all data and make them accessible for relevant teams.
  • Provide insights for historical data.
  • Provide insights in real-time.

On a much smaller scale, the data were sitting everywhere. Half the time, even the client didn't know where they were or what data they were collecting. Then came the issue of structuring all these data to provide the business intelligence they needed.

A fully automated solution

On a very high level, Sipher built a fully automated ETL solution and a data analysis platform to:

  • Enable our client's customers to understand their own data.
  • Enable internal teams to gain vital business intelligence from trends and patterns from customer data.

Sipher's task was to develop the platform and provide an end-to-end application lifecycle management — build, test, debug, deploy and manage platform.

Never settle for average

The team at Sipher managed to build everything the client wanted and much much more.

Our fully managed service allowed the client to focus on features rather than the infrastructure. On top of that, the ETL solution was optimized to handle a large set of data to reduce infrastructure cost.

By creating a centralized data pipeline and a unified platform for analytics and reporting for both real-time and historical data, we removed the need to maintain multiple systems — further reducing the cost on the client's end.

We weren't done with just these. The ultimate prowess of our engineering team came very unexpectedly as we navigated the project to create a self-sustaining and scalable platform. We ended with a fully automated data pipeline and a data analysis system that doesn't rely on any engineers to operate.

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