Data Performance & Quality
Boost your organization’s efficiency with high-performance data infrastructure. .
Modern businesses rely on swift, dependable access to their data. Our Data Performance & Quality services ensure that your infrastructure can handle growing data volumes and real-time processing demands with agility and precision.
Benefits
Accelerated data processing and reporting
Reduced system downtime
Optimized infrastructure costs
Future-ready architectures supporting AI & analytics
Our Business Partners In Data Performance & Quality
Infrastructure Optimization
Tailor system configurations for maximum throughput, resource efficiency, and low latency.
Real-Time Data Pipelines
Build high-speed data pipelines using Apache Kafka, Apache Flink, and similar technologies.
Cloud-Native & Hybrid Architectures
Design systems for seamless integration between cloud and on-premise data workloads.
System Health Diagnostics
Conduct ongoing system audits to identify performance bottlenecks and opportunities for improvement.
High-Availability & Disaster Recovery
Architect solutions that ensure uptime and recoverability in mission-critical scenarios.
Data Lake and Warehouse Optimization
Fine-tune data lakes and warehouses like Snowflake, Redshift, and BigQuery for performance.
Parallel Processing & Distributed Systems
Leverage Hadoop, Spark, and distributed computing to handle large-scale data processing.
Database Performance Tuning
Enhance SQL and NoSQL database responsiveness with indexing, partitioning, and memory optimization.
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Use Cases & Industry
Financial services: Accelerated end-of-day batch processing and fraud detection pipelines
Healthcare: Real-time patient monitoring and secure EMR systems
Manufacturing: IoT data ingestion and predictive maintenance performance tuning
E-commerce: Peak-season website and backend optimization
Resources
Industries We Serve:
Finance
Healthcare
Manufacturing
Telecom
Retail
Transportation & Logistics
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Featured Blogs
The Uprising of Self-Service Analytics
FAQs
It refers to ensuring fast, reliable access to data across infrastructure—building systems that scale, support real-time processing, minimize downtime, and optimize cost-efficiency.
Cresco provides infrastructure optimization, real-time pipelines (e.g., Kafka, Flink), cloud-native and hybrid architectures, system health diagnostics, HA/DR setups, data lake/warehouse tuning (e.g., Snowflake, Redshift), parallel processing frameworks (Hadoop, Spark), and database performance tuning.
Use cases span finance (accelerated batch processing, fraud detection), healthcare (real-time patient monitoring), manufacturing (IoT ingestion and predictive maintenance), and e-commerce (peak-season performance optimization).
Clients experience faster data processing, improved uptime, lower infrastructure costs, and architectures that are AI- and analytics-ready.
SQream is a GPU-powered analytics engine (comprising SQreamDB and SQream Blue) that accelerates querying and analytics over petabyte-scale datasets—transforming complex, large-volume workloads into rapid, cost-efficient operations.
SQream enables up to 80% faster processing than legacy platforms, significantly speeding up BI queries, batch jobs, dashboards, and reporting.
Its GPU-driven design allows for massive parallelism with a smaller hardware footprint, reduced cloud spend, and compressed data storage—streamlining performance and lowering total cost of ownership (TCO).
SQream accelerates data prep while enabling model training and inference with GPU efficiency—dramatically reducing model development timelines and resource usage.
Yes, in TPC-DS benchmark tests, SQream achieved up to 99× faster performance with linear scalability across 1 TB and 10 TB workloads using modest GPU setups.