Real-Time Analytics Strategy for Telcos

The telecommunications industry is experiencing unprecedented growth and transformation, driven by technological advancements, increasing customer demands, and evolving market dynamics. To stay relevant and competitive in this rapidly changing landscape, Telcos need to harness the power of real-time analytics. Real-time analytics provides Telcos with timely and actionable insights that empower them to make informed decisions, optimize operations, enhance customer experiences, and seize new business opportunities. This article explores the key reasons why Telcos need real-time analytics to stay relevant in the future.

  1. Meeting Customer Expectations:

In today’s digital era, customers expect personalized and seamless experiences. Real-time analytics enables Telcos to understand customer behaviors, preferences, and needs in real-time. By analyzing customer data in the moment, Telcos can personalize offers, proactively address issues, and deliver tailored services, ultimately enhancing customer satisfaction and loyalty.

  1. Optimizing Network Performance:

Telcos operate complex networks with numerous interconnected components. Real-time analytics enables them to monitor network performance, identify bottlenecks, and proactively address issues. By leveraging real-time insights, Telcos can optimize network capacity, reduce downtime, and ensure consistent service quality, leading to improved customer experiences and reduced churn.

  1. Enabling Real-Time Decision-Making:

In the fast-paced Telco industry, timely decision-making is critical. Real-time analytics provides Telcos with instant access to actionable insights, empowering decision-makers to respond quickly to market changes, competitive threats, and emerging opportunities. With real-time data at their fingertips, Telcos can make informed decisions that drive business growth, efficiency, and innovation.

  1. Enhancing Revenue Generation:

Real-time analytics helps Telcos identify new revenue streams and monetize their data assets. By analyzing customer usage patterns, behavior, and preferences in real-time, Telcos can offer personalized upselling and cross-selling opportunities, targeted advertising campaigns, and value-added services. Real-time analytics also enables dynamic pricing strategies, ensuring optimal revenue generation and profitability.

  1. Improving Operational Efficiency:

Telcos deal with vast amounts of data from various sources, including network devices, customer interactions, and operational systems. Real-time analytics streamlines data processing, enabling Telcos to gain immediate insights into network performance, service utilization, and operational efficiency. By optimizing resource allocation, predicting maintenance needs, and automating processes, Telcos can enhance operational efficiency and reduce costs.

  1. Proactive Fraud Detection and Security:

Real-time analytics plays a crucial role in detecting and preventing fraud in the Telco industry. By monitoring real-time data streams, Telcos can identify anomalies, patterns, and suspicious activities associated with fraud and security breaches. Real-time alerts and predictive models enable Telcos to take proactive measures to mitigate risks, protect customer data, and maintain a secure network infrastructure.

  1. Embracing the Internet of Things (IoT):

The proliferation of IoT devices presents both opportunities and challenges for Telcos. Real-time analytics allows Telcos to collect, analyze, and act upon the massive amounts of data generated by IoT devices. By leveraging real-time insights from IoT data, Telcos can optimize connectivity, manage network congestion, and deliver innovative IoT services that drive revenue growth and operational efficiency.

Real-time analytics is no longer an option but a necessity for Telcos looking to stay relevant in the future. By harnessing the power of real-time insights, Telcos can meet customer expectations, optimize network performance, enable timely decision-making, enhance revenue generation, improve operational efficiency, ensure security, and embrace emerging technologies. ClickHouse, a powerful analytics database, empowers Telcos to build real-time analytics solutions that drive business success in the dynamic Telco industry. By adopting real-time analytics, Telcos can stay ahead of the competition, deliver exceptional customer experiences, and thrive

☛ Quick facts on ClickHouse

  • Open Source ColumnStore with vectorised query computing capabilities 
  • Built for Massively Parallel Processing Systems, Large/complex queries can be run in parallel with minimal or no effort, The modern hardware infrastructure ready!
  • Data compression – ClickHouse supports data compression and this improves query performance.
  • Horizontally scalable columnar database system – ClickHouse is built for web-scale data analytics, Data can be replicated across several ClickHouse Shards. ClickHouse has distributed database analytics-ready columnar database system.
  • In ClickHouse, data is not just stored by columns but is also processed by vectors to achieve high CPU performance.
  • Web-Scale data analytics-ready – Primary keys are allowed, The data extraction for specific clients through Metrica counter over a specific time range makes low latency query analytics possible.
  • Flexible aggregation – Aggregate functions for partial data with approximated calculation (minimal data retrieval option). Random keys aggregation instead of all keys for higher accuracy using minimal resources.
  • Maximum availability and self-healing – Asynchronous multi-master replication with auto-failover capabilities.
  • SQL-based – ClickHouse supports SQL, JOINS, subqueries including FROM, IN, JOIN clauses; and scalar subqueries are allowed. Correlated subqueries are not allowed.

☛ Why do we recommend ClickHouse over many other columnar database systems?

  • Compact data storage – Ten billion UInt8-type values should exactly consume 10GB uncompressed to efficiently use the available CPU. Optimal storage even when uncompressed benefits performance and resource management. ClickHouse is built is store data efficiently without any garbage.
  • CPU efficient – Whenever possible, ClickHouse operations are dispatched on arrays, rather than on individual values. This is called “vectorized query execution,” and it helps lower the cost of actual data processing.
  • Data compression – ClickHouse supports two kinds of compression LZ4 and ZSTD. LZ4 is faster than ZSTD but the compression ratio is smaller.ZSTD is faster and compresses better than traditional Zlib but slower than LZ4.  We recommend customers LZ4 when I/O is fast enough so decompression speed will become a bottleneck. When using super ultra-fast disk subsystems you have an option to specify “none” compression. ZSTD is recommended when I/O is the bottleneck in queries with large range scans.
  • Can store data in disk – The columnar database systems like SAP HANA and Google PowerDrill can only work in the RAM.
  • Massively Parallel Processing – ClickHouse is capable of Massively Parallel Processing very large/complex SQL(s) optimally and cost-efficiently
  • Built for web-scale data analytics – ClickHouse supports sharding and distributed processing, This makes ClickHouse the most preferred columnar database system for web-scale. Each shard in ClickHouse can be a group of replicas addressing maximum reliability and fault tolerance.
  • ClickHouse support Primary Key – ClickHouse permits real-time data updates with a primary key (there will be no locking when adding data). Data is sorted incrementally using the merge tree to perform queries on the range of primary key values.
  • Built for statistical analysis and supporting partial aggregation – ClickHouse is a statistical query analysis-ready columnar database store supporting aggregate functions for approximated calculation of the number of various values, medians, and quantiles. ClickHouse supports aggregation for a limited number of random keys, instead of for all the keys. You can query on a part (sample) of data and generate approximate results reducing disk I/O operations considerably.
  • Supports SQL – ClickHouse supports SQL, Subqueries are supported in FROM, IN, and JOIN clauses, as well as scalar subqueries. Dependent subqueries are not supported.
  • Supports data replication – ClickHouse supports asynchronous multi-master and master-slave replication.

☛ Why do successful companies work with ChistDATA for ClickHouse Consultative Support and Managed Services?

  • ChistaDATA provides full-stack ClickHouse Optimization. We deliver elite-class Consultative Support (24*7) and Managed Services for both on-premises ClickHouse infrastructure and Serverless/Cloud/ClickHouse DBaaS operations.
  • ChistaDATA Server for ClickHouse (and all tools essential for Data Ops. @ Scale) will be Open Source (100% GPL forever) and free. We are committed to helping corporations in building Open Source ColumnStore for high-performance Data Analytics.
  • Global Team available 24*7 for ClickHouse Consultative Support and Managed Services.
  • Our team has built and managed Data Ops. Infrastructure of some of the largest internet properties. We know very well the best practices for building optimal, scalable, highly reliable and secured Database Infrastructure @ scale.
  • Lean Team Culture: Startup-friendly and specialists in DevOps. and Automation for Database Systems Maintenance Operations.
  • Transparent pricing and no hidden charges – We have both fixed-priced and flexible subscription plans.
  • Based out of San Francisco Bay Area. But, we have global teams operating from 11 cities worldwide to deliver 24*7 Consultative Support and Managed Services for ClickHouse.

☛ How can ChistaDATA help you build web-scale real-time streaming data analytics using ClickHouse?

  • Consulting – We are experts in building optimal, scalable (horizontally and vertically), highly available and fault-tolerant ClickHouse powered streaming data analytics platforms for planet-scale internet / mobile properties and the Internet of Things (IoT). Our elite-class consultants work very closely with your business and technology teams to build custom columnar database analytics solutions using ClickHouse.
  • Database Architect services – We architect, engineer and deploy data analytics platforms for you. We will take care of your data analytics ecosystem so that you can focus on business.
  • ClickHouse Enterprise Support – We have 24*7 enterprise-class support available for ClickHouse, Our support team will review and deliver guidance for your data analytics platforms architecture, SQL engineering, performance optimization, scalability, high availability and reliability.
  • ClickHouse Training.
About Shiv Iyer 206 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.