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Azercell is the first company applying Big Data technologies in the local communication sector

Azercell is the first company applying Big Data technologies in the local communication sector
22.05.2021 12:54

 
Azercell Telecom, which is the first to introduce Big Data technology in the communications sector of Azerbaijan, has made significant progress in this area. The use of advanced solutions in this area by the mobile operator has made its digital transformation possible. Currently, Azercell's target is to create models that determine the needs of subscribers in real-time and send them the appropriate offer immediately, thereby making life easier for their customers. That is why Big Data analytics is the foundation of any Azercell product today.
 
This technology, which creates unlimited opportunities for mobile operators, has eliminated the difficulties associated with the existing information platform, data storage, and processing. Big Data technology allows Azercell, which has a large amount of data, to conduct in-depth data analysis in real-time. It also responds quickly to changing market conditions and provides an opportunity to make immediate recommendations.
 
In order to fulfill the potential of this massively generated data company has launched big data initiative which consists of:
 
Technological transformation - first ever commercial realization of a big data technologies in the local communication sector
Analytical transformation - increase the effectiveness of analytical processes – visualization, real-time reporting, predictive analytics
Data assets management - foundation for corporate-level data governance (enterprise data catalog, business catalog, data quality tools)
 
To complement with increased data volumes and analytical needs Azercell implemented big data ecosystem around open-source technologies like Apache Hadoop, Spark, and Kafka. Data processing capabilities were increased by implementing the Apache Nifi data collection platform. At the same time, the Big Data platform has been integrated into one company-level corporate data storage platform.
 
Azercell had enriched analytical capabilities by implementing SAS and Tableau machine learning and visual analytical platforms. Application of these platforms enabled faster development of machine learning, predictive and statistical data models. As a result, a new churn model, dual sim models, segmentation models, and sales optimization models have been developed. This, in turn, allowed precise customer segmentation, churn prediction, and developing products and services that are more in line with market realities.
 
Developed corporate dashboards enable transparently and in near real-time to track key financial and business KPIs by all departments. Thus, the company's activities are now monitored online through special panels, and relevant decisions are made based on information about traffic, services, and other details in real-time. They provide an opportunity for prompt response to the changing market conditions and make immediate recommendations.
 
Besides enterprise software, Azercell is also developing new models and porting existing ones to open-source tools and libraries in R and Python. This strategy enriches analytical capabilities.
 
Azercell is implementing a data governance solution from a leading provider – Informatica. Implementation of this project will allow data to be managed, obtained, and classified.
 
Big Data technologies benefit both companies and customers - the better a company knows its target audience, the more advantages offers it can make to them or offer more personalized products. On the other hand, Big Data technology helps to optimize the internal decision-making process and reduce the overall cost of data processing. This ultimately results in more effective product prices. Big Data allows increasing competitiveness by taking advantage of previously unavailable opportunities and more accurate forecasting. It also provides an opportunity to create solutions that will further enhance the well-being of the society.
 

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