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I will fix slow quicksight dashboards e high AWS analytics costs
Analytics Engineer Sr
Data Analyst & Engineer with 9+ years in banks. Expert in SQL, Python, AWS & AI automation. Builds robust pipelines, dashboards & smart solutions to boost CRM, KPIs and business growth.
About this Gig
re your QuickSight dashboards slow, expensive, or putting pressure on your AWS infrastructure?
In most cases, the problem is not QuickSight itself, but how analytics workloads are designed, sourced, and scaled in AWS.
I help companies improve QuickSight performance while reducing AWS analytics costs, by identifying architectural bottlenecks across:
- Data sources (RDS, Aurora, Redshift, Athena)
- OLTP vs OLAP workload separation
- Query patterns and refresh strategies
- SPICE usage and data modeling
- Cost drivers hidden behind near real-time requirements
This is architecture-level consulting, not generic tuning tips.
Youll leave with a clear diagnosis, prioritized recommendations, and a cost-efficient path forward aligned with your data volume, user concurrency, and latency needs.
This is about designing analytics the right way not paying more AWS bills to fix the wrong architecture.
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FAQ
Is this just QuickSight tuning or dashboard optimization?
No. This service focuses on architecture-level performance and cost optimization. In most cases, slow dashboards are a symptom of how data is sourced and processed in AWS, not how visuals are built.
Will you tell me exactly which AWS services to use?
I provide recommendations based on your usage patterns, data volume, latency needs, and cost constraints. The goal is to define the right architecture, not to push a one-size-fits-all solution.
Can you help reduce AWS costs without hurting performance?
Yes — that’s the core of this service. By separating transactional and analytical workloads and aligning refresh strategies with real business needs, it’s often possible to improve performance while lowering costs.
Do you implement the solution or only provide guidance?
This gig focuses on diagnosis, architecture design, and optimization strategy. Implementation support can be discussed separately, depending on scope and complexity.
