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Data Warehouse (DWH)
- Provisioning, configuration, and optimization of complex/multi-layer data integration platforms
- Data at rest - protection; partitioning; obfuscation; multi-tenant environments
- Data at motion - encrypting; data-flow optimization
- Data at use - de-personalization; multi-dimension analytics; data regulation; compliance management
- Data acquisition management; planning; evaluation; optimization; parallelism; decoupling
- Data retention levels facilitation
- Setup, maintenance, and optimization of the application environment
- ETL job transformations
- Source/target governance
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Error-handling activities and adjustments to prevent future occurrences.
- Data access logging
- Data usage logging and monitoring
- Data auditing
- Process auditing and threat evaluation.
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Database patch management and maintenance
- Compatibility matrixes
- Clean-up
- Data auditing
- Back-up
- High Availability on data and process layers
- Disaster recovery planning
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Executive Information Systems (EIS)
- Decision support ruleset identification and management
- Data assets management, encapsulation and verifications
- Filtering, drill-down and drill-through
- Forecasting (trends) – ad-hoc trend manipulation and what-if scenarios
- Internal/External data assets identification and integration
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Analysis and Design Improvements / Hybridization
- Of existing DWH environments
- Of Corresponding reporting layers
- Of Pre-calculation areas, staging concepts
- Of Master Data concepts
- Implementation of practical optimisations (performance, data objects – tables, views, procedures, user functions, etc.)
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Translation of business requirements into technical architecture roadmap
- Design and develop the architecture for all data related components.
- Tools integration strategy
- Source systems data E/L(t) strategy
- Data Staging
- Movement and Aggregation
- Information and Analytics delivery
- Data Quality Strategy
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Architecture
- Multi-layered DWH Architecture, Design and Implementation
- Busines Intelligence and Business Analytics
- Deep Analytics (multi-source, in-memory)
- Performance management and Optimisation
- Data related components (ODS, EDW, DM, r/m/hOLAP, etc.)
- Metadata and Master Data Management (“golden record” implementation)
- Hardware recommendations, sizing and configuration
- RDBMS installation, configuration and tuning including on-premise/cloud
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Performance monitoring, optimization and refactoring of SQL scripts
- SQL scripts re-factoring
- Primary/foreign key adjustments
- Indexes
- Execution plan enforcement
- Parallelism
- Based on analysis and design – table space optimisations, disk groups, files and data itself optimisation (hot data, warm data, cold data)
