Data Analytics - Redshift

OneData Software’s Amazon Redshift–based Data Analytics offering empowers organizations to consolidate, model, and analyze massive volumes of structured and semi-structured data with high performance and minimal infrastructure overhead. As part of its AWS Data Analytics Services, OneData builds scalable, secure, and cost-efficient Redshift environments tailored to each client’s business goals

⚙️ Core Capabilities

Data Warehousing Architecture • Provisioning of Redshift clusters with columnar storage and massively parallel processing (MPP) • Integration with Amazon S3, AWS Glue, and Lake Formation for hybrid lakehouse architectures • Support for Redshift Spectrum to query S3 data without loading • Centralization of siloed data from ERP, CRM, logs, and applications into a BI-ready warehouse

ETL/ELT Pipelines & Data Modeling • Real-time and batch ingestion using AWS Glue, Kinesis, and Lambda • Schema design, transformation, and orchestration for optimized performance • Use of AWS CDK for automated provisioning and pipeline deployment

Advanced Query Optimization • Performance tuning via sort keys, distribution styles, and materialized views • Workload Management (WLM) for concurrent query handling • Compression encoding, vacuuming, and scheduling strategies to reduce latency and cost

BI & ML Integration • Seamless connectivity with Amazon QuickSight, Tableau, and Power BI • ML workflows using Amazon SageMaker for predictive modeling and inference • Support for JDBC/ODBC clients and self-service analytics interfaces

Security, Governance & Compliance • Enterprise-grade controls including IAM roles, VPC isolation, SSL encryption, and secret rotation • Federated identity provider support for secure access • Audit logging via AWS CloudTrail • Compliance alignment with HIPAA, PCI DSS, ISO 27001, and GDPR

Cost Optimization & Scalability • Deployment via Redshift Serverless for dynamic scaling • Reserved instance planning and usage monitoring • Tiered storage strategies and concurrency scaling • Proven cost savings of up to 40% through optimized architecture and scheduling

Industry Use Cases • Retail: Customer segmentation, sales forecasting • Finance: Risk modeling, transaction analytics • Healthcare: Patient data warehousing, compliance dashboards • Manufacturing: Sensor telemetry, production metrics

Managed Services & Support • Cluster lifecycle management and provisioning • Query performance audits and tuning • Ongoing monitoring, patching, and optimization • Governance dashboards and self-service analytics enablement