Case Study: Testing Data Lake Applications in Financial Services
公司规模
Large Corporate
产品
- GenRocket
- GSelf-Service
- GenRocket Real-Time Engines
技术栈
- Synthetic Test Data Generation
- Data Manipulation Language (DML)
- CI/CD Pipeline Integration
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
技术
- 分析与建模 - 数据挖掘
- 分析与建模 - 预测分析
- 功能应用 - 企业资源规划系统 (ERP)
适用行业
- 金融与保险
适用功能
- 质量保证
- 商业运营
服务
- 系统集成
- 软件设计与工程服务
关于客户
A multi-national banking and financial services corporation required comprehensive test data automation for testing its data lake applications. The company offers financial products for retail banking, direct banking, commercial banking, investment banking, wholesale banking, private banking, asset management, and insurance services. They operate in more than 40 countries and rank as one the world’s largest banks. Data lakes are repositories for large amounts of data collected from multiple sources in a raw and native format. They eliminate information silos by combining data from diverse sources such as electronic banking systems, IoT devices, social media sites, and internal-collaboration systems. Data may be stored in structured, semi-structured or unstructured formats. Increasingly, banks are using data lakes to turn big data into actionable business intelligence to drive profitable business outcomes. Electronic data is growing at a phenomenal rate due to the rise in online banking and digital transformation of the customer experience.
挑战
The Bank issued a Request For Information (RFI) to evaluate a test data solution that would enable multiple teams to perform a complete range of testing operations in a highly efficient and scalable manner. They focused on synthetic test data generation because of the ability to produce highly controlled data variations in multiple data formats and its inherent data security. They were looking for a solution that would meet their needs for automated unit testing, exhaustive functional testing and performance testing procedures. GenRocket responded to the RFI with a complete Test Data Automation solution and participated in a rigorous Proof of Concept (POC). The combined RFI/POC process included several test data challenges. They were incorporated into four use cases that reflect their application testing requirements. They also wanted to evaluate the management and scalability of the system. The POC requirements are briefly outlined below. System Setup and User Account Management The Bank required a platform to provide control over access to the system and its resources. They also required reporting on various aspects of system operations.
解决方案
GenRocket worked closely with one of its global IT services partners to jointly conduct the POC with the Bank. The process showed how GenRocket can combine speed of provisioning with full control over data quality in a way no other test data solution can match. This successful POC resulted in the selection of GenRocket as the best solution for the Bank’s Data Lake testing requirements. Several GenRocket capabilities combined to make this evaluation a success. Modular Architecture GenRocket’s component based architecture provides the flexibility to design any variation or volume of test data with assured referential integrity. Powerful data generators and receivers allow the Bank’s QA team to conduct exhaustive testing with extensive control over data combinations, patterns and permutations. The ability to query external data sources allowed testers to combine real-world production data with controlled synthetic data. The use of synthetic data provided total security and compliance with privacy laws. Model-Based Test Data Because GenRocket’s test data is based on the customer’s data model, any database schema, DDL file, or a metadata contained in a CSV file can be used to structure test data that accurately reproduces the original database or file format. Data models can be imported and immediately used to define test data scenarios for generating real-time test data on-demand.
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Real-time In-vehicle Monitoring
The telematic solution provides this vital premium-adjusting information. The solution also helps detect and deter vehicle or trailer theft – as soon as a theft occurs, monitoring personnel can alert the appropriate authorities, providing an exact location.“With more and more insurance companies and major fleet operators interested in monitoring driver behaviour on the grounds of road safety, efficient logistics and costs, the market for this type of device and associated e-business services is growing rapidly within Italy and the rest of Europe,” says Franco.“The insurance companies are especially interested in the pay-per-use and pay-as-you-drive applications while other organisations employ the technology for road user charging.”“One million vehicles in Italy currently carry such devices and forecasts indicate that the European market will increase tenfold by 2014.However, for our technology to work effectively, we needed a highly reliable wireless data network to carry the information between the vehicles and monitoring stations.”
Case Study
Safety First with Folksam
The competitiveness of the car insurance market is driving UBI growth as a means for insurance companies to differentiate their customer propositions as well as improving operational efficiency. An insurance model - usage-based insurance ("UBI") - offers possibilities for insurers to do more efficient market segmentation and accurate risk assessment and pricing. Insurers require an IoT solution for the purpose of data collection and performance analysis
Case Study
Smooth Transition to Energy Savings
The building was equipped with four end-of-life Trane water cooled chillers, located in the basement. Johnson Controls installed four York water cooled centrifugal chillers with unit mounted variable speed drives and a total installed cooling capacity of 6,8 MW. Each chiller has a capacity of 1,6 MW (variable to 1.9MW depending upon condenser water temperatures). Johnson Controls needed to design the equipment in such way that it would fit the dimensional constraints of the existing plant area and plant access route but also the specific performance requirements of the client. Morgan Stanley required the chiller plant to match the building load profile, turn down to match the low load requirement when needed and provide an improvement in the Energy Efficiency Ratio across the entire operating range. Other requirements were a reduction in the chiller noise level to improve the working environment in the plant room and a wide operating envelope coupled with intelligent controls to allow possible variation in both flow rate and temperature. The latter was needed to leverage increased capacity from a reduced number of machines during the different installation phases and allow future enhancement to a variable primary flow system.
Case Study
Automated Pallet Labeling Solution for SPR Packaging
SPR Packaging, an American supplier of packaging solutions, was in search of an automated pallet labeling solution that could meet their immediate and future needs. They aimed to equip their lines with automatic printer applicators, but also required a solution that could interface with their accounting software. The challenge was to find a system that could read a 2D code on pallets at the stretch wrapper, track the pallet, and flag any pallets with unread barcodes for inspection. The pallets could be single or double stacked, and the system needed to be able to differentiate between the two. SPR Packaging sought a system integrator with extensive experience in advanced printing and tracking solutions to provide a complete traceability system.
Case Study
Transforming insurance pricing while improving driver safety
The Internet of Things (IoT) is revolutionizing the car insurance industry on a scale not seen since the introduction of the car itself. For decades, premiums have been calculated using proxy-based risk assessment models and historical data. Today, a growing number of innovative companies such as Quebec-based Industrielle Alliance are moving to usage-based insurance (UBI) models, driven by the advancement of telematics technologies and smart tracking devices.
Case Study
MasterCard Improves Customer Experience Through Self-Service Data Prep
Derek Madison, Leader of Business Financial Support at MasterCard, oversees the validation of transactions and cash between two systems, whether they’re MasterCard owned or not. He was charged with identifying new ways to increase efficiency and improve MasterCard processes. At the outset, the 13-person team had to manually reconcile system interfaces using reports that resided on the company’s mainframe. Their first order of business each day was to print 20-30 individual, multi-page reports. Using a ruler to keep their place within each report, they would then hand-key the relevant data, line by line, into Excel for validation. “We’re talking about a task that took 40-80 hours each week,” recalls Madison, “As a growing company with rapidly expanding product offerings, we had to find a better way to prepare this data for analysis.”