Big Data

With the rapid development of the Internet, the amount of data generated by various applications within an enterprise is increasing rapidly. Big Data refers to technologies and initiatives that involve data that is too diverse, fast-changing or massive for conventional technologies, skills and infrastructure to address efficiently.

The 3V’s of Big Data

  • Volume: This signifies large amounts of data.
  • Variety: This refers to the evolving types and growing sources of data, including semi-structured and unstructured data. Big data technologies provides horsepower that accelerate these processes, thereby making data provisioning and usage faster, too.
  • Velocity: Velocity in the context of big data refers to the speed of data acquisition, and processing.

Big data is everywhere and has become an unavoidable challenge in real life. While the big data slowly shows people the great opportunities for academia, industry and government, it also poses challenges to the parties involved:


How to collect and manage the disorganized data?


How to build up a complex platform for big data storage and computing?


How to ensure the data security?


How to analyze the data and build up modeling?


How to present the visualization and assist business in decision-making?


What roles are involved in big data, and what processes should be built up?

Our advantages

Big Data Tools

The Company (Starlight & SMS) provides a series of big data tools, including data crawling, real-time computing, machine learning and other functions and modules, which allows users to quickly choose the right technology and build the big data business platform.

Sound Data Management System

Strict control is done over data standards, metadata, data quality, and data security so as to ensure that the data can be used efficiently.

Well-developed Management Process

With years of experience in development and verification, the Company has prepared a set of construction and management methods to provide complete process and corresponding strategy on planning, design, construction. Many successful cases can be found in areas such as data standard design, metadata design, and quality management processes, and such case can help users learn experience from the best practice and quickly build their own business platform and management system in big data.

Customer Cases


Home Partners' Lease with a Right to Purchase Program allows customers to find a home that they want to rent from HPA initially, but may also like to buy in the next three to five years. This business model places a higher demand on identifying target market of real estate and defining prospective customers. In order to solve these problems effectively, we have set up data model clustering based on data on real estate and customers and clearly outlined the market regions and customer portraits which best suit the demand of the HPA business model, which in the end has effectively helped the Marketing Department formulate its marketing strategies. In the meantime, we set up a tenant behavior forecasting model based on the historical data on tenants' rent-paying details and on their communication with HPA staff. The model can accurately identify whether the tenant have any default risk in rent paying or any possibilities to renew the lease when the duration is expired, which can HPA prepare the solutions ahead of schedule, reduce the tenant default risk and vacancy rate, and lower the operating costs of HPA.

  • 1. Affiliate Scoring Model: Comprehensive scores will be calculated by integrating factors such as rate of on-time delivery and customer satisfaction, and such score will be applied in the recommendation of the subsequently services.
  • Self-analysis Platform: We do not only accelerate the efficiency of data operations, but also provides an open platform for business thinking, business expansion, and management innovation by means of self–service tools on data access, exploration and presentation. This can increase the security and effectiveness of data application and increase the value of data asset of the company.
  • Log Monitoring Service: Services logs of the business system are collected to apply cluster analysis and pre-warn the company.
  • User Behavior Analysis: User behavior logs are collected to track and analyze the commonly used operations, concerns, access path by the customers, and to define user portraits.
  • Automatic Order Dispatching Service: A work order can be automatically: dispatched to one affiliate by considering factors including the service time of this order, skills of the technician, driving distance, and availability of the service technician.