- 業界
- Financial Services
- 会社の規模
- +200,000
- ロケーション
- Global
ポイント
- Fast data ingestion: Ingests over 1TB of data daily, with access to 100-500TB of historical data.
- Actionable insights: Utilizes KX's actionable analytics for predictive analytics, anomaly detection, and big data processing.
- High-performance queries: Achieves low-latency queries for real-time decision-making across departments.
- ROI within 12-18 months: Demonstrated millions of dollars in value and a quick return on investment after deployment.
Bank of America faced significant challenges with its existing data systems, primarily a lack of flexibility in processing and analyzing large volumes of structured data. The financial institution needed a solution that could not only scale with its data growth but also deliver faster queries and enhanced analytics.
The challenge
The lack of flexibility in their existing infrastructure limited the bank’s ability to perform real-time analytics, anomaly detection, and predictive analytics on their vast data sets. They needed a solution that could handle large data volumes and deliver high-performance analytics to support decision-making across various business units.
Why KX?
Bank of America turned to KX for its powerful real-time data platform, capable of ingesting over 1TB of data daily and accessing up to 500TB of historical data. By leveraging our time series capabilities, low-latency queries, and q language, it achieved enhanced anomaly detection, predictive analytics, algorithmic automation, asset monitoring, and more.
The bank chose KX over competitors like Timescale and MongoDB due to its unique combination of speed, flexibility, and scalability. The deployment of KX technology on-premises helped the bank realize millions of dollars in value, achieving ROI within 12-18 months.
Discover how to transform data processing, analytics, and decision-making for banking and financial institutions.
Key statistics
- Data Ingested Daily: More than 1TB
- Historical Data Accessed: 100TB – 500TB
- ROI Timeframe: 12-18 months
- Development Cycle Improvement: 100%+ faster development cycles
- Query Performance Improvement: 100%+ faster query performance
Q/A
A: The primary challenge was the lack of flexibility in our previous systems. We needed a platform that could handle large volumes of data and provide real-time insights for decision-making.
A: KX has allowed us to ingest over 1TB of data daily and analyze large historical datasets, making our operations faster and more efficient. The actionable analytics and low-latency queries have significantly improved our data-driven decision-making.
A: The time series capabilities, vectorized data, and low-latency queries are key features that have allowed us to process large datasets and gain real-time insights for anomaly detection and predictive analytics.
A: We evaluated solutions like Timescale and MongoDB, but KX stood out due to its superior performance and flexibility in handling large-scale data analytics.
A: We achieved ROI within 12-18 months after deploying KX on-premises.
