Over the years, how MNOs and MVNOs use data has dramatically evolved. This is primarily due to digital transformation and the expansion and availability of big data. This shift has seen Telcos turn to data management solutions to help better utilise the data available to meet customers’ needs effectively. Below we answer the question, “How are MNOs and MVNOs utilising data management solutions, and what are the best practices and strategies for this?”
Understanding Data Management for MNOs and MVNOs
It is no secret that MNOs and MVNOs have access to vast amounts of consumer and network data. This includes data related to Call Detail Records (CDRs) and any other events occurring in the network, such as recharging, billing, subscriptions, donations of airtime, subscriber information and more. Due to the ever increasing requirement to get a 360 view of the subscribers, additional data sources are also ingested and used to understand subscriber behaviour, which includes social media interactions, mobile money transactions, and any other additional supplementary subscriber data.
The data that MNOs and MVNOs need to manage have specific characteristics that include:
- Volume – refers to the amount of data in terms of the mass quantities that Telcos are trying to harness, which will improve decision-making. In this digital age, Telcos need to utilise high volume of data and large data sets, traditionally, volumes included megabytes, gigabytes, and trillions of bytes, but today, we are now measuring bytes in petabytes and zettabytes.
- Velocity – refers to data in motion or the speed at which data is created, processed, or analysed. Today, there is a need for low latency, fast and real-time access to large amounts of data and insights.
- Variety – to get a complete view of your big data as a Telco, you need to collect and analyse different types of data and data sources. These various data sources will allow you to pull relevant insights about your business, operations, and customers.
- Value – the value of data management and big data analysis lies in identifying the valuable and relevant data needed for actionable insights and information.
From the above, it is clear that data holds immense value for MNOs and MVNOs as it provides more insight into customer needs and wants. Armed with this data, Telcos can effectively deliver value-added services, improve customer experience and operational efficiency. As these additional insights are gathered, the requirement to have these insights readily available to multiple divisions within business, as a single source of information, is also ever increasing.
There is no doubt that this kind of data can help Telcos increase their revenue, but if the data is not managed effectively, then the insights will hold no value. So, the question we now need to answer is how does a Telco ensure that the data they are using is complete, accurate and valuable? The answer lies in ensuring that the best practices for data management, governance, and security are followed.
Best Practices for Data Management
The data warehouse is one of the most essential data management components for MNOs and MVNOs. In simple terms, a data warehouse is a data management system that houses large amounts of network and customer-related raw data. This data usually comes from various sources, and the data warehouse centralises and consolidates this data into a “single source of truth”. The data warehouse is a fundamental aspect of advanced analytics as it supports business intelligence activities. It enables data analysts to design data models dependent on the Telco’s needs and derives valuable insights from this data.
There are three specific types of data warehouses that include:
- On-premises data warehouse – has been the go-to data warehouse choice for many Telcos over the years. The Telco must purchase, deploy, and maintain all hardware and software with an on-premises data warehouse. They are popular because they offer improved governance, security, data sovereignty, and better latency.
- Cloud data warehouse – a cloud data warehouse uses the cloud to ingest and store data from different sources. This data warehouse has no physical hardware. It is software as a service. These data warehouses offer scalability, ease of use and are often more cost-effective than on-premises data warehouses.
- Hybrid Cloud \ On-premises data warehouse – certain parts of the data is kept on-premises, for security and cost effectiveness, and other parts of the data is moved to cloud storage, either for retention purposes, or for additional big data ingesting, mining, analysis and reporting.
No matter which data warehouse a Telco chooses to utilise, several best practices must be followed to ensure the insights derived are complete, accurate and relevant. These best practices include:
- Data modelling and architecture – data modelling is used to create rules for the relationships between the data entities within the data warehouse. In this way, data modelling identifies the different data entities needed to produce specific analytics. The data architecture process is slightly different. It looks at the database in its entirety and assists in identifying the tools and solutions needed to store, process and analyse the data.
- Data quality management – refers to measuring how well the data sets meet the set-out criteria for accuracy, completeness and relevance. This ensures that the insights derived from the data are correct and complete.
- Data security and access controls – refer to safeguarding all the data within the warehouse from unauthorised access or theft. This includes all hardware, software, storage devices, user devices and access controls.
The above best practices ensure that the data is optimised correctly and that the data being pulled is relevant and complete. This is vital to having the correct analytics and insights needed for effective decision-making.
The quality of the insights and analytics are not only impacted by the best practices mentioned above but by the movement of data from the different sources into the data warehouse and the data transformation process. This is what we refer to as the ETL (Extract, Transform and Load) process. Below we dive deep into this process and why it is essential to data management for MNOs and MVNOs.
ETL Process Strategies for MNOs and MVNOs
ETL is short for “Extract, Transform and Load” and is essential to the effectiveness of business intelligence (BI) processes and systems. The ETL process is vital to data management as it allows for collection, processing and data organisation from different sources into one place.
The data can then be used to analyse network, performance, customer behaviour and other key metrics. This is made possible by the specific data models and rules in place. Through the ETL process MNOs and MVNOs can gain insight into business performance, highlight opportunities for improvement and facilitate informed data-driven decision-making. In this way, the ETL process can allow Telcos to better understand and manage data.
The ETL process consists of three specific stages, which include:
- Extract – CDRs and network event data are extracted from several sources and transferred into a data staging area.
- Transform – The data extracted from source servers is often raw and unusable in its original form. This data needs to be cleaned, mapped and transformed.
- Load – Once the data has been cleaned and transformed, it can be moved from the staging area to the data warehouse.
In simple terms, the ETL process gathers and consolidates raw data from multiple and relevant data sources. The data is then loaded into a data warehouse using tools like Adapt IT Telecoms CDRlive technology. While in the data warehouse, the data is indexed, partitioned and structured for performance. It is vital that the technology chosen offers scalability and can ensure uptime with the vast amounts of data that are being imported.
Various ETL strategies can be utilised as part of this process. These include:
- Automation and scheduling – the automated ETL process and scheduling tools enable IT teams and data scientists to perform ETL tasks without manual intervention. All tasks associated with this process are automated and scheduled.
- Data profiling and cleansing – refers to the detailed analysis of the source data to try to understand the data’s structure, quality, content and relationship.
- Error handling and logging – refers to tracking the data in relation to its source, destination, time of extraction and transformation to identify any errors that may have occurred during the process.
- Change data capture and synchronisation – this data strategy is related to tracking and capturing changes made to the data within the data warehouse. This allows for the identification and extraction of modified data to utilise the correct data for analytics and insights.
- Data encryption for sensitive customer data – data security is vital to the ETL process. Data is often encrypted using various methods to protect sensitive customer data.
When the right ETL strategy is implemented and the right tools are in place MNOs and MVNOs can experience the following benefits:
- Timely access – refers to the quick accessibility and access to the integrated and modified data needed to make informed data-driven decisions.
- Improved quality and consistency – the ETL process can assist with identifying and correcting mistakes, inconsistencies and other issues related to the data. This process ensures that data is cleaned and transformed so that the quality is accurate, reliable and dependable.
- Reduced likelihood of human errors – by utilising this technology instead of manual processes, you can manage the risk of human error, which can significantly affect the quality of the data and insights produced from that data.
Undoubtedly, the ETL process is an invaluable tool for data management, especially for MNOs and MVNOs. However, it is vital that the right tool and solution be chosen to reap the full benefits of ETL and gain real access to insights that will transform your Telco business.
Conclusion
In today’s digital age MNOs and MVNOs have access to big data, which can be instrumental in improving customer experience, increasing revenue, developing new product offerings and enhancing operational efficiency. Access to this data is impressive, but not having the right data management tools, ETL processes, and best practices in place will mean you cannot access accurate, relevant and data-driven insights related to your business. In our competitive digital world, you, as MNOs and MVNOs, need to ask, “Are you utilising and managing your data in the most effective way possible to grow your business?” If you answered no, then contact us today. Let us help you utilise your data to increase your revenue and drive profitability.
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I’m the Advanced Analytics Solution Stream Owner at Adapt IT Telecoms. With my years of experience in the ICT industry, I have gained skills in various areas including Sales, Strategy, Professional Services, Management, Cloud, and Digital Transformation. My team and I specialise in providing niche large data solutions to markets such as mobile network, education, and regulatory. As the Solution Stream Owner, I’m responsible for ensuring that we deliver top-notch services and innovative solutions to our clients. My journey in this field started as a technical engineer and over the years, I have moved into pre-sales, business development, consulting, analytics, commercial, and operations management. This has given me a diverse set of skills, which allows me to have conversations that lead to innovative solutions. What I’m most passionate about is the integration between software and people, both within society and organisations. It’s a challenge, but one that I find extremely rewarding. I’m committed to ensuring that we continue to provide cutting-edge solutions that help our clients stay ahead of the competition.
