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Qlik > Case Studies > Setting a benchmark for security industry
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Setting a benchmark for security industry

Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Finance & Insurance
Applicable Functions
  • Business Operation
Use Cases
  • Predictive Quality Analytics
  • Real-Time Location System (RTLS)
Services
  • Data Science Services
  • System Integration
The Challenge
CSC Financial Co., Ltd (China Securities) needed to better understand asset movements in real-time to maximize investment strategies. It also wanted to provide its clients with a real-time display that would clearly show the status of their portfolio from the China Securities application and other investment channels. The company had to deal with large data volumes and many databases which required up to 18 replication tasks. Frequent system upgrades also meant that replication environments had to be constantly rebuilt and replicating from heterogeneous databases was a cumbersome operation.
About The Customer
CSC Financial Co., Ltd (China Securities) is a major national securities company providing high-quality financial services to government, corporate, institutional and individual investors. Having earned an excellent reputation, it was awarded the highest Class AAA rating by the China Securities Regulatory Commission and has retained that rating for 12 years. The company needed to copy data from many sources and unify it to present clients with a clear visualization.
The Solution
To solve its problems, the company formed a cooperative venture with Qlik and Shanghai DingKui Information Technology (DingKui) using Qlik Replicate’s real-time data synchronization solution. The resulting solution combines the advantages of Qlik Replicate with DingKui’s industry knowledge. It allows China Securities to collate the data rapidly and automatically from multiple systems such as gold, OTC trading, stock options and margin trading. The data is replicated to Apache Kafka stream processing platform and then aggregated on a Spark Big Data platform. The unified analysis is carried out through a Redis in-memory database and data is available for real-time client asset analysis.
Operational Impact
  • Provides a unified task operation and monitoring interface which allows staff to see immediately whether or not a task has been successfully built
  • Automates configuration and use processes to achieve zero manual input, increasing efficiency and reducing errors
Quantitative Benefit
  • Increase the speed at which we can display real-time client asset data to the sub-second level

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