With the rising demand for network connectivity, service providers are forced to scale rapidly and adopt new technologies. As a result, network complexities and data silos increase, posing serious challenges for network engineers and operation teams.
In addition, data silos and limited visibility force service providers to allocate resources to collect data from disparate systems manually. It causes a delay in decision-making and troubleshooting and hinders network rollout.
What should service providers do to help their network engineering and operations teams reduce rollout time, avoid performance issues, and go beyond detecting problems?
33% acceleration in network designing
67% reduction in troubleshooting time
Simpler and faster operational processes
A leading provider of advanced network communications and technology solutions for consumers, small businesses, enterprises, and carrier partners across the U.S., was facing a similar challenge.
Due to rapid network expansion across multiple locations, the client had ended up with a complex network, with data scattered over multiple systems and geographies. Disjointed data hindered their ability to gain business intelligence, impacting their speed of decision-making and progress.
These issues led to inefficient resource utilization, ineffective network troubleshooting, and delays in new network rollouts.
Prodapt’s data visualization solutions helped the client steer through data complexities and leverage data to gain business insights.
Due to multiple acquisitions over time, the client had ended up with heterogeneous systems which complicated reporting and analytics of their network data. They had scattered sets of data integrated from various disjointed systems and were unable to trace the customizations done on their network systems.
Siloed and disorganized data jeopardized the efficiency of their network engineering team, Network Operation Centre, and business users
Prodapt started with implementing frameworks that could streamline the extraction and ingestion of data from heterogeneous sources into a graph database, enabling real-time data visualization. This facilitated data-driven decision-making for the respective stakeholders.
We used hierarchical graphical visualization for faster troubleshooting, impact assessment, and acceleration of network rollouts. In addition, we built web-based geographical data mapping and analysis to trace the shortest/optimized route for truck rolls.