Solutions for Telecommunications Industry

Telecommunication market penetrates into various industries and telecommunication operators can access to a massive amount of user data, so that telecommunication operators have obvious big data advantages.

But, with the "gold mine" of big data in hands, how do telecommunication enterprises find their new profit growth points and diversified competition? How can they get the maximum benefit from big data?

1.1Market Environment

The Chinese telecommunication industry has entered into an era of "stock competition" in a situation of tripartite confrontation.

China Mobile, China Unicom and China Telecommunication are the three major carriers like the three legs of a tripod. The demographic dividend of the telecommunication industry has disappeared and growth space for new users will become more and more narrowed. Carriers are waging war on fees, advertising and technology. For how to provide high quality products and quality service in such harsh environment, the stock users have become the next competitive point in the telecommunication industry.

Competition pattern in the telecommunication industry is also changing that OTT(Over The Top) service providers starts swallowing telecommunication industry. Globalization tendency of telecommunications. Globalization trend of carriers and telecommunication services.

In the future, how to provide customers with good customer experience and benefit from existing customer assets becomes a key factor in the telecommunication industry.

1.2Data Environment

China has hundreds of millions of users playing computers, tablets, mobile phones and other digital devices, and data from trading, social networking and GPS are coming out every day. The telecommunications market permeates every industry, and telecommunication operators can access to a large number of customer data.

China has hundreds of millions of users playing computers, tablets, mobile phones and other digital devices, and data from trading, social networking and GPS are coming out every day. The telecommunications market permeates every industry, and telecommunication operators can access to a large number of customer data.

How to use data "gold mine" in hands to cultivate their own core information competitiveness and gain the maximum benefit in the historical vicissitude is the key to the competition of telecommunication operators.

1.3Internal Environment

From the market competition to the stock competition, replacement of business tax with value-added tax VAT for the telecommunication business tax results in a huge impact on the original profit model. Profitability declines, the original main profit business loses the advantage, and how to quickly find new profit point and cultivate user flow will become the key.

1.4 Data - aided operators gain competitive advantage

Competition and change require operators to increase their earnings from "business-driven" to "data-driven". Data - aided decision - making is the key to the future development of operators. Operators have years of accumulation in data.

In aspect of data diversity, operators data cover all businesses such as mobile voice, fixed telephone, wireless internet and fixed network interference, etc, involving family and the public and corporate clients while collecting channel access information such as electronic channels, entity channel and direct sales channels, etc., in all types. For data application, telecommunication operators hold all the aces.

How to use data optimization infrastructure construction to construct and optimize network operation management for better infrastructure services;

How to use data to master the market direction and improve the marketing conversion rate, so as well serve for market and sales;

How to use data to improve service quality and prevent user loss, and manage the service and customer life cycle;

How to use the data to monitor abnormal business operation and grasp the market operation condition, to business operation and operating management;

How to use data to open the door toward external commercialization, find a new path to obtain new revenue model?

Data visualization is the first step in data usage.

Real self-service platform, distributed storage,
with stable and efficient performance

The characteristics of Yonghong Tech solutions for telecommunication industry:
distributed storage, high hardware availability, architecture"not shared" or exploratory self-service analysis.

2.1Characteristics of data in telecommunication industry

·Data islands: data are stored separately in different branches, and different business data of branches are stored independently.

Large data volume: data in large size are diverse and complex. The daily trading data is in the hundreds of billions, and covers hundreds of dimensions including business and users, etc.

Diversity of business: involving customer data of transaction, social contact and GPS, and data of enterprise internal operating maintenance, operation and so on.

2.2difficulties in telecommunication industry data

Unification and integration of data : unify and integrate data across regions and business, while guaranteeing data quality. And authenticity and correlation of the data should be consistent.

Big data storage: storage of mass data guarantees speed of storage, reading and accessing, and guarantee the hierarchical authority of data reading.

Big data analysis: resource management of existing analytical model, generation of exploratory and self-service model for the unknown model.

2.3Scheme of data visualization system architecture of telecommunication industry

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2.4Project Characteristics

Distributive storage: facilitate horizontal extension of the whole architecture, capable of linearly horizontal expansion without performance impact, guarantee flexible scalability of performance and capacity, solve the storage problem of large data volume.

Distributive storage: facilitate horizontal extension of the whole architecture, capable of linearly horizontal expansion without performance impact, guarantee flexible scalability of performance and capacity, solve the storage problem of large data volume.

"Unshared" architecture: distributive machine nodes are independent from each other, and distributed data centers are independent from distributed data marts to avoid resource contention, ensure the architecture to run efficiently and stably in response to different computing demands, such as real-time computing, off-line computing, and streaming computing, etc.

Exploratory self-service analysis: independent data service and analysis services can be achieved for unknown and flexible business need.

Lightweight modeling to ensure data integrity.

Share the pressure of distributed data center by the way of distributed data mart at the upper layer of data center,
and distributive column-stored data mart concentrate more system resources on data retrieval and distributed computation,
using lightweight modeling to eradicate frequent model changes and data re-extraction from the root model
due to demand change.

3.1Value of Yonghong

Storage -- solve highly concurrent and high I/O bottleneck of distributed data center:

The core problem of distributed architecture is highly concurrent and high 1/0 in the system operation. Share the pressure of distributed data center by the way of distributed data mart at the upper layer of data center.

Calculation -- MPP data mart for analytical data:

As a data warehouse, distributed data center has to share data storage, computation and other data requests. It is necessary to balance the resources with the functions of adding, deleting, changing, checking and calculating data. Yonghong MPP data mart is a distributed columnar-stored data mart dedicated to analytical data, which centralizes more system resources on data retrieval and distributed computation. At the same time, columnar storage guarantees independence and integrity of data in storage and invocation.

Data visualization -- front end of exploratory self-service analysis:

Yonghong BI in comparison with the pain points of traditional BI uses lightweight modeling to eradicate frequent model changes and data re-extraction from the root model due to demand change. At the same time, front end of Yonghong BI provides a visual modeling approach which can easily achieve cross-database and cross-source data connections. The visual business modeling operation page can quickly complete the business analytical model by simply dragging over and clicking points. The visualization report generated can realize data linkage and data screening, which makes data presentation become the first step for data analysis and enables the further exploration analysis after visualization to continue, so as to fully release data value.

Yonghong Z-Suite one-stop big data analysis platform can create values for our customers and make them achieve success based on excellent data techniques.