Amazon Web Services
AWS Smart Analytics Services
Give every decision maker fast, trustworthy answers with dashboards, natural-language analytics and real-time insights built on AWS.
Turn AWS Data into Everyday Decisions
Collecting data on AWS is the first step; turning it into decisions people make every day is the goal. Smart analytics combines a governed semantic layer, well-designed dashboards, natural-language questions, streaming insights and analytics embedded into the applications where people work. On AWS, Amazon Quick Sight, now part of Amazon Quick (formerly Amazon QuickSight and Quick Suite), delivers dashboards and generative BI, Amazon Athena and Amazon Redshift serve SQL at any scale, and Amazon Kinesis with Amazon Managed Service for Apache Flink handles real-time analysis.
Hanoi Technology designs analytics around the decisions you need to support. We define metrics with business owners, model data for performance and clarity, and build dashboards and alerts that people actually open.
The Challenge
Why Analytics Often Underdelivers
Plenty of dashboards exist; trusted, used ones are rarer.
Conflicting Metrics
Different teams calculate revenue, active users or margin differently, and meetings spend time debating numbers instead of acting on them.
Dashboards Nobody Uses
Reports built from requirements lists rather than real decisions get viewed once and forgotten, while users export data to spreadsheets.
Slow Queries and Stale Data
Dashboards on poorly modeled data or nightly batch loads are too slow or too late for operational decisions.
Analytics Locked in BI Tools
Customers and frontline staff need insights inside the applications they use, not in a separate BI portal they rarely visit.
Business Value
What Smart Analytics on AWS Delivers
One Version of the Truth
Shared datasets and semantic definitions ensure that every dashboard calculates key metrics the same way.
Answers in Plain Language
Generative BI capabilities in Quick Sight let users ask questions in natural language and build visuals, executive summaries and data stories.
Real-Time Visibility
Streaming pipelines with Kinesis and Managed Service for Apache Flink power dashboards and alerts that update within seconds or minutes.
Scalable, Serverless Performance
Athena, Redshift Serverless and the Quick Sight SPICE engine scale with demand without capacity planning by your team.
Embedded Insights
Quick Sight embedding puts dashboards and natural-language Q&A directly into your SaaS product or internal portals.
Search and Log Analytics
Amazon OpenSearch Service supports log analytics, observability and full-text search over operational data.
Start from the Decision, Not the Data
The most useful analytics begin with a question: what decision does this person make, how often, and what would change it? We design metrics, visuals and alerts from that question backward, which keeps scope focused and adoption high.
Our Services
Hanoi Technology’s End-to-End AWS Smart Analytics Services
Analytics engineering, BI and real-time insights on AWS.
Analytics Strategy and KPI Design
We work with business owners to define decisions, KPIs and metric definitions, then map them to data sources and ownership.
- KPI catalog
- Metric definitions
- Analytics roadmap
Data Modeling and Semantic Layer
We model data in Redshift or Athena using dimensional and dbt-based approaches, and create shared Quick Sight datasets and topics.
- Dimensional models
- dbt project
- Shared datasets
Dashboards and Self-Service BI
We design and build Quick Sight dashboards, paginated reports and natural-language topics, with row-level security and governance.
- Dashboards and reports
- Row-level security
- User training
Real-Time Analytics
We build streaming pipelines with Kinesis Data Streams, Amazon MSK and Managed Service for Apache Flink, feeding operational dashboards and alerts.
- Streaming pipelines
- Real-time dashboards
- Alert rules
Embedded Analytics
We embed Quick Sight dashboards and Q&A into your applications with multi-tenant security and usage-based scaling.
- Embedding architecture
- Tenant isolation
- Product analytics
BI Migration
We migrate reports from legacy BI tools to Quick Sight, consolidating duplicates and validating results.
- Report inventory
- Migrated dashboards
- Validation results
Our Approach
How We Deliver Smart Analytics
A decision-driven process that brings users in early.
- 01
Understand Decisions
We interview users, observe how they use current reports and identify the decisions analytics must support.
Deliverables: Decision map · Prioritized KPIs
- 02
Model the Data
We design data models and metric definitions, and confirm data quality for the selected KPIs.
Deliverables: Data model · Data quality checks
- 03
Prototype Dashboards
We build interactive prototypes quickly and test them with real users before finalizing designs.
Deliverables: Dashboard prototypes · User feedback
- 04
Build and Secure
We finalize dashboards, configure permissions and row-level security, and optimize performance.
Deliverables: Production dashboards · Security configuration
- 05
Drive Adoption
We train users, monitor usage and iterate based on what people actually use.
Deliverables: Training materials · Usage reports
Use Cases
AWS Analytics Use Cases
Examples of analytics we build on AWS.
Executive KPI Dashboard
Leadership sees revenue, margin, pipeline and operational KPIs in one Quick Sight dashboard with drill-down to regions and products.
Delivery Operations Monitoring
Dispatchers watch live order volumes, courier positions and delays through a streaming dashboard and receive alerts on bottlenecks.
SaaS Customer Analytics
A SaaS provider embeds usage dashboards into its product so customers can see adoption and outcomes for their own accounts.
Marketing Attribution
Campaign, web and sales data combine in Redshift to measure channel performance and spending efficiency.
Log and Security Analytics
Application and access logs flow into OpenSearch Service for troubleshooting, anomaly detection and audit queries.
Self-Service Questions
Sales managers ask natural-language questions about their territory and receive charts without waiting for an analyst.
Technology
Analytics Technologies on AWS
Services we use to build analytics solutions.
- Amazon Quick Sight
- Amazon Quick
- Amazon Athena
- Amazon Redshift
- Amazon OpenSearch Service
- Amazon Kinesis Data Streams
- Amazon Data Firehose
- Amazon MSK
- Amazon Managed Service for Apache Flink
- AWS Glue
- Amazon S3
- Amazon SageMaker Unified Studio
- dbt
- Amazon CloudWatch
Platforms
Analytics Platforms We Combine with AWS
Why Hanoi Technology
Why Organizations Choose Hanoi Technology
Senior, Cross-Functional Teams
Strategy, data, AI, cloud and engineering specialists work as one team, so nothing is lost between hand-offs.
Proven Delivery
More than 50 projects delivered for clients in North America, Europe and Asia-Pacific.
Radical Transparency
A written update every week and a demo of working software every sprint, so you always know where things stand.
Cost-Effective Global Delivery
Experienced engineers from our Hanoi delivery hub, with working-hour overlap for every major time zone.
Success Story · Food delivery
AI dispatch and live tracking for a food delivery startup
A fast-growing urban food delivery startup was losing customers to slow deliveries at peak times. We built AI order dispatching and connected restaurants, drivers and customers in real time.
Read the Full StoryMore Success Stories
Real estate
+38%lead conversion rateProperty discovery and lead conversion for a US real estate marketplace
A US marketplace connecting buyers, sellers and agents had plenty of traffic but few enquiries. We built personalized property discovery, AI valuation and a one-tap route to contact an agent.
E-commerce and retail
+32%conversion ratePersonalized shopping experience for a US fashion retailer
A fast-growing US fashion and lifestyle retailer had plenty of traffic but a 2.1% conversion rate. We combined a recommendation engine with a simpler path from discovery to checkout.
Resources
Featured Resources
Industry trends and practical guidance to help you get more value from data, AI and technology.
FSMA 204 After the Delay: Using Shipment Monitoring to Get Traceability-Ready by 2028
The FDA Food Traceability Rule deadline moved to July 2028, but the data work is large. Here is how to use shipment monitoring and event data to get ready without wasting the extra time.
CSRD After the Omnibus: What the Revised ESRS Mean for Reporting From 2027
The Omnibus and the simplified ESRS reshaped EU sustainability reporting in 2026. Here is who is in scope, what changed in the standards and how to adapt your data and process.
OpenTelemetry in 2026: Building a Vendor-Neutral Observability Strategy
OpenTelemetry has become the default way to collect telemetry. Here is what changed in 2026 and a practical roadmap for a vendor-neutral observability stack.
Make Your Data Answer Real Questions
Book a free consultation and tell us which decisions you want to improve. We will suggest metrics, data sources and a first dashboard we could deliver quickly.
AWS Smart Analytics FAQ
What happened to Amazon QuickSight?
In late 2025 AWS evolved Amazon QuickSight into Amazon Quick Suite, a broader workspace combining BI with AI-powered research, knowledge and automation features, and the offering has since been presented as Amazon Quick. The BI capability continues as Amazon Quick Sight, with dashboards, paginated reports, embedding and natural-language analytics. Existing dashboards and datasets continue to work, and we help clients understand which capabilities and licenses they need.
Should we query data with Athena or Redshift?
Athena is serverless and charges by data scanned, which makes it ideal for ad hoc queries over the S3 data lake and for moderate dashboard workloads. Redshift is better for high-concurrency BI, complex joins and predictable performance on large curated datasets. Many architectures use both: Athena for exploration and Redshift for heavily used dashboards. We decide based on query patterns, concurrency and cost.
Can we embed dashboards in our own product?
Yes. Quick Sight supports embedding dashboards, visuals and natural-language Q&A into web applications, with authentication through your application and row-level security to isolate each customer’s data. We design the tenant model, embedding flows and capacity approach, and integrate analytics into your user experience so it feels like a native product feature rather than an external tool.
How do you ensure metrics are consistent?
We define each KPI with business owners, document the logic and implement it once in a shared model, using dbt or curated Redshift views, and shared Quick Sight datasets. Dashboards then reuse these definitions rather than recreating calculations. Changes go through review, and we add tests that check key figures against expected values after every data refresh.
What does analytics on AWS cost?
Costs depend on query engines, data volumes and users. Athena charges by data scanned, Redshift by serverless usage or provisioned nodes, and Quick Sight by user or capacity-based pricing models. Streaming services charge by throughput. Efficient data modeling, partitioning and caching keep query costs low. We provide estimates for your expected usage and set up cost monitoring from the start.
How quickly can we have a first dashboard?
If the required data is already accessible on AWS, a first production dashboard for a focused set of KPIs often takes a few weeks, including requirements, modeling and user testing. If data must first be ingested and cleaned, add time for pipelines. We prefer starting small with one important decision, proving value and expanding from there.