Analytics consulting for modern teams
Turn scattered data into curated insights you can trust.
ChatterLytics helps you ingest, store, model, and visualize data— so stakeholders get clear answers, faster.
Ingestion
Reliable pipelines
Storage
Scalable foundations
Modeling
Metric clarity
Dashboards
Decision-ready
Services
End-to-end analytics support—from raw data to business impact.
Data ingestion
Connect APIs, databases, event streams, and files into dependable pipelines. I focus on clear ownership, observability, and incremental loads so your data arrives on time and in the right shape.
Data storage
Design a storage layer that scales with your business—whether that’s a warehouse, lakehouse, or a pragmatic hybrid. The goal is governed access, sensible cost controls, and fast queries.
Data modeling
Build a semantic layer that standardizes definitions (metrics, dimensions, entities) and prevents spreadsheet drift. Your team gets a single source of truth and models that are easy to extend.
Dashboards & insights
Deliver dashboards that answer real questions and survive scrutiny. I pair strong UX with trustworthy numbers—plus the narrative and analysis needed to drive decisions, not just views.
About ChatterLytics
ChatterLytics was founded by Amiyo Chatterjee to solve a simple problem: most companies have data, but very few use it to drive decisions.
Amiyo has built analytics systems at high-growth startups like OpenStore and Lendbuzz, and has worked with institutions including Morgan Stanley, Goldman Sachs, and State Street—bringing a mix of startup speed and enterprise rigor.
He’s hands-on across the full stack (SQL, modeling, dashboards, experimentation, product analytics) with one goal: outcomes—faster decisions, fewer guesses, and data you can trust.
What you can expect
- Clear scope, crisp deliverables, and a plan you can maintain.
- Pragmatic tool choices aligned to your team and budget.
- Documentation and handoff so you’re not dependent on me.
- Focus on business outcomes—not just data plumbing.
Contact
Tell me a bit about your data stack and what you’re trying to achieve. I’ll reply with next steps.
Typical engagements
Analytics foundations • data modeling • dashboard rebuilds • KPI definition • pipeline reliability
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