Legacy to Cloud-Based: Migrate from legacy databases to modern cloud solutions (AWS,
Azure, GCP)
On-Prem to Cloud: Transition on-premises databases to cloud-native or hybrid models for
flexibility
Version Upgrades: Upgrade database platforms to newer versions for enhanced security and
features.
Architecture Redesign: Re-architect databases for improved scalability, performance, and
reliability.
Microservices Implementation: Adopt microservices architecture for modern, efficient
database applications.
Schema Optimization: Optimize database schemas and data models to support contemporary
use cases.
Bottleneck Resolution: Resolve performance issues using indexing, query optimization, and
tuning.
Caching Strategies: Implement caching to reduce latency and boost response times.
In-Memory Databases: Leverage in-memory databases for real-time processing and faster
analytics.
Cloud Integration: Integrate databases with AWS, Azure, or Google Cloud for scalability
and flexibility.
Data Lakes & Warehousing: Build data lakes and warehouses for advanced analytics and
BI.
ETL Processes: Implement seamless ETL workflows for data integration across platforms.
IaC for Databases: Automate database deployment and management using Infrastructure as
Code (IaC).
CI/CD Integration: Integrate database workflows with CI/CD pipelines for continuous
updates.
Monitoring & Alerts: Implement automated monitoring and alerting for proactive database
management.
Enhanced Security: Strengthen security with encryption, access controls, and regular
audits.
Data Masking: Protect sensitive information through data masking and anonymization
techniques.
Regulatory Compliance: Ensure databases meet industry standards like GDPR, HIPAA, and
PCI-DSS.
Automated Backup: Set up automated backup and recovery solutions to maintain data
integrity.
Disaster Recovery Plans: Implement DR plans with failover mechanisms for business
continuity.
Cloud-Based DR: Utilize cloud solutions for cost-effective disaster recovery with minimal
downtime.