According to global technology intelligence firm ABI Research, data and analytics services revenue is expected to grow from US$140 million in 2021 to US$6.4 billion in 2026, at a CAGR of 115 percent.

“数据正在成为一个重要的生产要素，数据收集，存储，处理以及对数据的经济细节的理解是提供挑战和机遇的关键股。通过数据和分析重视创建键，CSP应采用基于标准的分析函数，以推动其运营的可操作见解，“Abi Research的高级分析师5G核心和Edge网络。

网络数据分析功能(NWDAF), for example, is an analytics function that provides operational intelligence, streaming, and data collection. Guavus and Sandvine are two vendors, among others, that offer full-featured and vendor-agnostic NWDAF capabilities that enable CSPs to place data and analytics at the heart of their innovation model. Also, NWDAF functionality is a stepping-stone for CSPs to build analytics functions that propel them forward in the digital economy. “In a digital economy where applications and APIs rule supreme, CSPs seek to become data-driven organizations. They should apply analytics at multiple ‘stations’ of the network spanning core, transport, and edge locations,” Alusha advises.

Orange, for example, claims that by the end of its Engage2025 strategic plan, most of its employees will have undergone data and AI awareness training. Every CSP will have a different foundation to build from and a different strategy. However, a common denominator among them is to leverage analytics functions, such as NWDAF, to change the structure of current systems and processes to produce more of what is desirable and less of that which is undesirable. There are challenges, particularly around best practices and obtaining the relevant human capital. But CSPs that rise to these challenges first may well gain a competitive advantage in the market.

CSPS.do not seek a one-time attempt at innovation but rather sustainable productivity growth as a source of competitive advantage. With 5G, cloud, and big data analytics, the industry has the external catalysts that can drive new growth and innovation. But CSPs, and the broader industry, need to realize that growth will come from combining and rearranging existing (cellular) technologies with big data and analytics. New use cases need to be assessed on business impact and complexity in terms of skills required to deliver them. In addition to having the right tools and analytics functions (e.g., NWDAF), success for CSPs will come from how they use those tools. Orange, Telefonica, Vodafone, and Verizon are among the many CSPs investing to obtain the right know-how.

If CSPs are to be effective at using 5G big data and analytics, they should pursue a path that aligns with their unique circumstances. “It will not be so much about a 5G data platform and analytics as it will be about establishing the right operational context, for example, a fitting culture where everyone in the company seeks for ways for big data and analytics to enhance operations. At present, CSPs’ investments fall under two categories: one, buy out of the box models that improve execution and results of their product logic and operations; and two, buy analytics functions and big data models that have a positive impact on business results, for example, improve market share, improve revenue and sales, and explore new revenue streams,” Alusha concludes.

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