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CAPGEMINI SE

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Capgemini : Telcos' data analytics transformation

12/03/2021 | 09:52am EST

Data analytics is a key element in the digital transformation within the telecommunications industry. It enables better decisions, more automation, and stronger feedback, as well as the ability to deliver better customer relationships, more personalized experiences, higher quality of service, and more efficient and automated network operations.

The problem? For many CSPs their existing data infrastructure is no longer adequate for addressing new data demands and challenges, including data democratization, access to advanced analytics tools and external data sharing. While migrating the data estate to the cloud has proven effective in many sectors, doing so is particularly challenging for organizations like CSPs that hold large volumes of data of high complexity.

In this post, we focus on realizing the data analytics transformation of CSPs, and explore seven facets of the benefits brought by the cloud. 1. Data access

In many Telco organizations, data can be difficult to access. It resides in silos across brands, departments and technologies, making it difficult for the business to consolidate and analyze information and create timely, relevant insights. Democratizing data is hard and costly. The cloud can make it much easier for organizations to unite data from various sources. It provides higher processing capabilities and easily available storage to make timely, accurate, relevant data accessible to all users. This, in turn, can help the business make more informed decisions, personalize the customer experience, and develop and offer new services. By providing higher storage and processing capabilities, the cloud also makes data accessible to all departments. It is also possible to provide access on a more granular level and allocate access on demand based on data classification and security rules, regardless of data origin. The cloud also empowers data users by enabling self-service capabilities as well as an on-demand analytical environment.

2. Data volume and cost controls

To generate insights from high volumes of data, organizations must move, store, and process them across all networks, application, platforms, and tools. This requires a high-capacity, flexible storage platform, which can be cost prohibitive. A cloud architecture offers an opportunity for Telcos to control costs while managing high data volumes. Through the cloud, near limitless resources can be spawned on demand. Organizations pay only what the business consumes, and resources can be scaled up or down based on variable needs. Finally, most hyperscalers also offer proactive recommendations based on analytics budget tools for correct sizing and optimization strategies, helping Telcos manage costs and optimize budgets.

3. Intelligent decisioning and automation

To provide "ATAWAD"-anytime, anywhere, any device - services and customer attention, Telcos must be capable of at-scale real-time intelligent decisioning and automation. Artificial intelligence (AI) use cases can be complex to develop, deploy and industrialize. They require dedicated technical platform expertise to install and manage, which many Telcos do not have currently and lack the time to build. These technologies also require further hardware and software investments. Once again, the cloud can help address this issue. When partnering with a hyperscaler, the organization has access to secure and scalable machine learning (ML) platforms that will establish access to any data platform environment within minutes. Telcos can leverage a full range of leading-edge tools and pretrained ML/AI models, without any need for installation or complex configuration. Finally, industrialization of use cases becomes far easier as the tools can be used to support the MLOps best practices, deliver full automation, enable repeatable experiments and facilitate operations.

4. Data ecosystems

Telcos are some of the most data-rich companies in the world. As such, these organizations have the opportunity to contribute to data ecosystems with third parties in order to monetize their insights. But the barriers to sharing data are significant: data must be documented and of good quality, with verification and correction procedures applied. In addition, organizations must comply with security and privacy regulations. Traditional data sharing is often complex, costly, and not inherently secure. Cloud hyperscalers and some software vendors such as Snowflake offer new ways to share data. They create a storage mechanism, granting access rights and enforcing data sharing policies with any number of consumers without having to copy or move the data. They also provide tools to facilitate the implementation of sound data governance and data quality practices. In so doing, it becomes easier for Telcos to share and ultimately monetize their data - without compromising privacy, security or compliance.

5. Cost allocation

In a traditional IT environment, it can be difficult to attribute costs to certain groups or functions, which means that the IT expense is shared across all users regardless of consumption or shouldered by a select group of users. Furthermore, since the platform is usually fixed cost and fixed capacity, there are limited incentives to optimize individual processes. The cloud provides far more flexibility to organizations in terms of budgets and billing. Hyperscalers group resources with their own denomination, subscription, management group, or resource group. Organizing capabilities in this way is an effective way to monitor service consumption while also supporting the budget plan and identifying deviations.

6. Agile consolidation

The Telco industry has gone through numerous rounds of mergers and acquisitions (M&A) and consolidation. This has created incongruent technologies and solutions, with a heavy technical debt, which is stymying innovation. Cloud platforms help organizations perform their transformation with the best agile and DevOps practices. Capabilities include: leveraging advanced and accessible development tools; allowing development teams to easily spawn environments and implement infrastructure-as-code; and providing a full range of robust analytics capabilities. In this way, Telcos can create cloud-native, autonomous development teams. These development teams can go fast, iterate and reduce dependency on external groups.

7. Heterogeneous data structures

As noted above, Telcos own immense amounts of heterogeneous data. Some of this information is fully structured, while other crucial sources, like activity logs, are semi-structured. Standardizing these data sources too early or aggregating them incorrectly could lead to loss of information, including those insights the company was hoping to capture. Cloud platform allows storage and conservation of data in a large variety of unprocessed, raw formats. Then it can be delivered to multiple specialized databases which are dedicated to different use cases. Transformations are implemented efficiently in automated pipelines. As seen in this post, the cloud provides many valuable benefits for Telcos. However, understanding the potential of the cloud and realizing its value are two different things.

Our companion paper, The cloud imperative for Telco data, reviews the many facets of cloud migration that Telcos must consider as they formulate their plan, choose priorities and identify a transformation partner that will help them seize this opportunity.

TelcoInsights is a series of posts about the latest trends and opportunities in the telecommunications industry - powered by a community of global industry experts and thought leaders.

Authors:

Yannick Martel, Group offer lead for Data & AI in the Telecom industry

Nicolas Claudon, Customer First Group offer lead within the Data & AI portfolio

Disclaimer

Capgemini SE published this content on 03 December 2021 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 03 December 2021 14:51:00 UTC.


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