Data Wrangling Makes Expected Performance and Deep Insights Possible for Network Optimization.
The future giants of telecom will be those who deliver the best customer service, at scale, with effective personalization. But to do this, telecom companies must prioritize network optimization.
Network optimization is about improving IT performance and reducing network strain in order to minimize costs and increase data flow. Within telecoms, network optimization is based not only on hardware stack and system architecture, but also on the ever-changing data consumption and network bandwidth pulled by subscribers. Striking a balance between data strategy and the customer experience is critical to success, but like any balancing act, it’s easier than it looks.
As the volume and types of data—structured, semi-structured, and unstructured—have proliferated within the telecom industry, the difficulty in predicting network bandwidth has similarly increased. What demands will the Netflixes and Skypes of the world place on telecom companies? Today’s telecom analysts need to be able to immediately synthesize high volumes of unstructured/semi-structured and third-party-sourced data to define and maintain that balance.
The Benefits of Network Optimization
The fundamentals of telecom won’t change: market giants provide the best perceived product at the lowest possible cost. Network optimization can help on both sides of the equation: costs and revenue. On the cost side, network optimization can be achieved with faster and better understood data analytics and insight into usage, network logs, hardware maintenance, marketing efficiency, peak load analysis, and near real time, granular levels of analysis that were previously impossible to do at scale.
Revenue growth in network optimization can come from combining disparate customer data silos into one source of truth. Using detailed records, app logs, social posts, satisfaction and call center data, brand insights and sentiment data in the same analysis makes it possible to derive insights never before accessible. That data can be used to enhance the customer experience by better predicting loads and providing faster download speeds, minimizing churn, optimizing existing offerings, and developing new products either alone or in concert with partners.
Network Optimization for Telecoms Is Challenging
If it was easy, everyone would be doing it. But network optimization in telecom companies is especially hard. Siloed data across multi national corporations, with different regulatory and legacy systems, combine to create an environment where data can’t flow easily among its various stakeholders. Telecoms have in some cases been collecting data for over 50 years, and that data may not be in a form that modern data scientists are used to seeing and working with. A data cleansing process may be required, which further slows down the regular dispersion of data into the telecom organization.
In addition, telecom companies aren’t alone in facing governance issues and data access challenges, internal politics and culture that hinder the flow of information, and bottlenecks in IT departments due to staffing and talent shortages. Once the data is actually obtained, then the average analyst will spend up to 80% in data preparation tasks, which creates further barriers to insight.
Trifacta Powers Better Telecom Network Optimization
Trifacta was created to enable real-time data synthesis and democratize the data analysis process, even within telecom’s extremely diverse and comprehensive data landscape. Telecoms can lessen the burden on IT departments, simplify the data wrangling process, and accelerate time to insights derived from complex customer, network, and billing data. This saves time, resources, and allows telecoms to provide the level of network optimization its subscribers increasingly require.
- Lessen IT Burden: Allow non designers to access data from nearly any source, protect data lineage, and lessen the need for precious development time for ongoing analytics support.
- Big Data Friendly By Design: Trifacta’s data wrangling solution was created to handle the large data volumes of data, where manipulating gigabytes or terabytes of data is commonplace. Trifacta’s high-performance data wrangling engine, Photon, enables faster feedback on greater volumes of data, which leads to huge productivity gains for all of our users. In addition, Trifacta’s Intelligent Execution Architecture maintains support for a growing list of modern data processing engines, such as Spark, Google Data Flow and MapReduce.
- Interactivity. Easy-to-use, interactive visuals—like the profiling page and data quality bar— make validation easier. Our interface then allows users to clean the data with a few simple clicks, rather than laborious programming.
- Automation. Future at-scale validation scripts for data quality issues become automated and performed by default once Trifacta is familiar with your data.
With Trifacta, analysts are empowered to interact with data in ways they never thought possible and leverage those insights for faster, better decision-making and network optimization. Learn more about Trifacta schedule a demo.