BY MENG QINGGUANG, CHIEF ARCHITECT

(tmforum 2015/16 Perspectives)

Challenges to CSPs Who Use Big Data

According to observation, the year 2015 has become the beginning of a new era – business-driven big data. The core characteristics of the new-era big data analytics system will be business-driven. Technologies like Cognitive Computing will become the core factors of the new big data analytics platform.

Facing the new era, communications service providers (CSPs) lack big data related skills and data analysts, and therefore are facing a lot of challenges when applying big data:

• Data asset integration: Various service and analysis systems are deployed in CSPs’ networks, including the BI, NI, CRM etc. These systems implement data analysis separately (which means in silos) by themselves, which is the largest obstacle to the success of big data analysis. Efficiently integrating data from varied domains and ensuring the data quality have become the most crucial tasks for CSPs.
• Lack of data analysts: Research shows that there were about 200,000 vacancies for big data analysts in the US in 2014. There is also a shortage of professionals in other areas which is an issue for CSPs needing to support refined business operation analysis.
• Shortage of successful use cases: CSPs have tried various methods to apply big data to business issues, with limited success.
• Difficulty in finding an appropriate business model for monetization: Data not only supports CSPs’ internal, advanced operations, but also assists them in the construction of digital ecosystems. Many CSPs have made attempts at data monetization, but few have succeeded in generating new revenues due to a lack of effective business models.

POSITIONING OF HUAWEI UNIVERSE BIG DATA ANALYTICS SOLUTION

As the core engine that drives CSPs’ digital transformation, big data is of vital importance. CSPs typically have the following questions when building big data analytics platforms:

• How to build a big data analytics platform?
• How to use the big data analytics platform to solve business issues?
• How to use the big data analytics platform to build a digital ecosystem and realize asset monetization?

Focusing on these questions, Huawei relies on its advantages (industry experience, technical strength, and excellent services) to build an optimal big data analytics solution Universe for CSPs, which consists of the Universe Analytics Platform and end-to-end (E2E) services. The Universe Analytics Platform includes the Data Factory, Wisdom Center, and Data Operation Platform, while E2E big data service includes the consulting service, data operation, data analysis as a service, data governance, and integrated delivery.

UNIVERSE ANALYTICS PLATFORM – DATA FACTORY

The Data Factory provides the following core features to solve the issue of data asset integration: unified data ingestion & integration, unified data asset management, unified data access.

Unified data ingestion and integration allows CSPs to adapt to more than 190 types of data sources in BSS, OSS, and MSS domains. It also provides adapters for collecting data from new media sources such as SNS, which assists CSPs with advanced analytics. The Data Factory supports automatic data cleansing and transformation, improving data integration efficiency.

Unified data access eliminates differences between interfaces at the data storage layer that contains the EDW, MPP DB, and Hadoop, and provides a unified access entrance for upper-layer applications. More importantly, it implements unified data access control, ensuring the security of data.

With the Data Factory, CSPs integrate various data sources from the BSS, OSS, MSS domains and real-time events, and complete data governance within three months – which is much shorter than that of traditional methods.

UNIVERSE ANALYTICS PLATFORM – WISDOM CENTER

Previously, data scientists were needed for commercial big data analysis. Now, the wisdom center provides real-time and intelligent data analysis through its knowledge discovery engine and real-time analysis and decision-making engine.

The business issue-oriented knowledge discovery engine, for example, the Persona engine, is developed based on technologies such as automatic modeling, incremental learning, and multi-dimensional feature extraction. This engine implements automatic knowledge discovery, shortening business analysis time from weeks to hours.

The real-time analysis and decision-making engine can process millions of events per second, based on automatic pattern-matching technologies, to help CSPs seize new opportunities.

The wisdom center also comes up with more than 300 out-of-the-box business cases, covering the Innovation and Growth, Customers and Markets, and Operation and Support business perspectives. The wisdom center has become an on-demand virtual data scientist team for CSPs.

With the help of the wisdom center, CSP S has increased its 4G marketing success rate from 5 per cent to 12 per cent boosting the number of subscribers and 4G service revenues significantly.

UNIVERSE ANALYTICS PLATFORM – DATA OPERATION PLATFORM

The data operation platform includes partner management, data product development, data exchange and transaction, and data product store.

Based on the data operation platform, the Huawei inTouch? partnership program helps CSPs quickly aggregate digital data operation ecosystems, create new business models, and realize data monetization.

Huawei cooperates with partners and CSP U to launch data monetization products, serving industries including finance, government, retail, etc. The data monetization products contain customer preference analysis, customer traffic analysis, advertisement effect evaluation, industry indexes etc. These products help CSP U open up new revenue sources.

E2E BIG DATA SERVICES

Huawei Universe provides the following E2E big data services:

• Consulting: Huawei cooperates with world-leading consulting companies in providing commercial and technical consulting for CSPs. The consulting services cover various scenarios including precise marketing, CEM, data operation, and technical planning of the big data analytics platform.
• Data operation: Partners from industries including advertising, banking, transportation, etc. are aggregated to provide a one-stop data operations service for CSPs.
• Data analysis: Huawei provides a business issue-oriented data analysis service, based on technologies such as data mining, machine learning etc.,.
• Data governance: This is implemented based on Huawei’s in-depth insight into telecom data and includes data governance maturity assessment, rule configuration, roadmap planning, and implementation.
• Integrated delivery: Implemented through Huawei’s service platform, the service reduces the complexity caused by technology fragmentation, and streamlines delivery.