Leading Fintech Eliminates Analytical Silos with OLAP on BigQuery
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Kyvos
- MicroStrategy
- Google BigQuery
Tech Stack
- OLAP
- Cloud Computing
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Cost Savings
Technology Category
- Analytics & Modeling - Big Data Analytics
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Services
- Data Science Services
- Cloud Planning, Design & Implementation Services
About The Customer
The customer is a US-based financial technology services company with a worldwide reach spanning over 100 countries. The company processes more than 50 billion transactions annually, providing payment services to approximately 3.5 million merchants and business locations, including retailers and financial institutions. Despite having uniform data, the company was facing challenges in creating and automating a single consolidated view of all its data for hundreds of users. The company was using 20 different cubes for core reporting, which was leading to siloed reporting due to the inherent limitations of the analytical environment. The company was also facing challenges in terms of high time-to-insights, as the time to publish the cube, even for a single data source, exceeded 6 hours. Changes in data or incremental refreshes required full reprocess downtime, which took over 24 hours, and users could not access the system for this duration. The company had maxed out the capacity of their Google environment and was spending massive amounts on cloud computing.
The Challenge
The US-based financial technology services company was struggling with creating and automating a single consolidated view of all its data for hundreds of users. Despite having uniform data, reporting was siloed due to the inherent limitations of the analytical environment. They initially attempted to build MicroStrategy intelligent cubes from data residing in Google BigQuery. However, there were limits on the amount of data each cube could hold. As a result, they were forced to split their data and create separate cubes for combinations of geographic regions and data sources. This led to an inability to get a single consolidated view of their data as they were using 20 different cubes for core reporting. The time to publish the cube, even for a single data source, exceeded 6 hours. Changes in data or incremental refreshes required full reprocess downtime. Reprocessing took over 24 hours, and users could not access the system for this duration. They maxed out the capacity of their Google environment. Despite running on a large server, there was no room for additional data. They were spending massive amounts on cloud computing.
The Solution
Kyvos helped the company consolidate 20 intelligent MicroStrategy cubes into a single cube for all data sources, geographic regions, and merchant information. Cloud-native, Smart OLAP™ technology enabled aggregations on a much broader dataset to build a holistic cube versus piecemealing smaller cubes. With a single cube approach, Kyvos enabled 1.6 Billion total fact records aggregated in the Kyvos cube, 2.4 Million unique Merchant IDs and 840K unique Customers IDs, 25 months of historical data, 90-minute cube build time, and Query response SLA <10 seconds. Besides, Kyvos eliminated in-memory limitations as it stores the cube on Google storage. Kyvos expanded the horizon of MicroStrategy to build the OLAP layer directly on the cloud. A single cube had the entire structure of dimensions, measures, and hierarchies. Users could plug in MicroStrategy directly into the Kyvos cubes and instantly access the Kyvos semantic layer. There was no need to do any manual settings or recreate the cube. They could pull everything from Kyvos. Performance improved substantially as instead of plugging MicroStrategy directly on BigQuery, they could now get their queries answered from the Kyvos cube itself. This also helped control compute costs and save on MicroStrategy usage.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
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
Enhancing Security and Compliance in Remitly's Global Money Transfer Service with Fastly
Remitly, an online remittance service, was faced with the challenge of securing its proprietary global transfer network. The company needed a security solution that could meet PCI requirements and protect customers' sensitive transactions through its mobile application. The solution had to be capable of defending against new and emerging attack types without impacting performance. Remitly also had to deal with irregular traffic patterns, such as a sudden spike in account transfers from a small network segment on the Pacific coastline of South America. The company needed to determine in real time whether such traffic indicated an attack or valid requests. A traditional web application firewall (WAF) would not be able to distinguish this traffic, potentially leading to customer frustration if the IP was blacklisted.
