FalconX Tech
FalconX Tech
IT Services & Consulting
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Engineering Practice

Data Analytics & Business Intelligence.

Most businesses sit on years of valuable transactional, behavioural, and operational data — and use almost none of it. FalconX Tech designs and builds the entire modern data stack: ingestion with Fivetran/Airbyte, warehousing on Snowflake/BigQuery/Redshift, transformation with dbt, and executive dashboards in Looker, Power BI, Tableau, or custom React. We also build the predictive models — churn, demand, fraud, LTV — that drive operational decisions, and the AIOps pipelines that monitor those models in production. Our analytics engagements have unlocked ₹140Cr+ in measurable revenue and cost-saving for clients to date.

Next.js 14TypeScriptPostgreSQLAWSDockerRedis
~/falconx/app/api/checkout
import { stripe } from "@/lib/payments";
import { db } from "@/lib/db";
import { z } from "zod";

export async function POST(req: Request) {
  // validate · authorize · persist · respond
  const { cart, user } = await schema.parse(req);
  const session = await stripe.checkout.create({
    line_items: cart.items,
    mode: "payment",
    metadata: { userId: user.id },
  });
  await db.orders.insert({ ...session });
  return Response.json(session);
}
✓ deploy · production · 1.2s build
What's in the stack

Built for real production load

Six engineering pillars, each with shipped reference implementations available on request.

🗄️

Data Warehouse & Lakehouse

Snowflake, BigQuery, Redshift, and Databricks Lakehouse architectures optimized for query speed and cost.

🔀

ETL / ELT Pipelines

dbt + Airbyte/Fivetran pipelines unifying 50+ data sources with sub-hour latency and full lineage tracking.

📊

BI & Executive Dashboards

Looker, Power BI, Tableau, and custom React dashboards with drill-down, alerts, and embedded analytics.

📈

Predictive ML Models

Churn prediction, demand forecasting, fraud detection, LTV modelling — built in Python and deployed via MLOps.

📻

Real-Time Data Streaming

Kafka, Kinesis, and Flink-based streaming pipelines for live dashboards, fraud detection, and IoT telemetry.

⚠️

AIOps & Intelligent Monitoring

ML-driven observability that detects anomalies, predicts incidents, and reduces alert fatigue by 80%.

Decision Speed

Faster executive decisions enabled by real-time dashboards vs. weekly spreadsheet reports.

+23%
Revenue Impact

Average revenue uplift attributed to data-driven pricing, segmentation, and retention strategies.

99.7%
Data Quality

Data accuracy and freshness SLA achieved after our governance and pipeline standardization programs.

Sprint Rhythm

From main to mainstream

SPRINT 01

Data Audit & Strategy

Map all data sources, assess quality, and identify the top 5 high-value analytics use cases by ROI.

SPRINT 02

Stack Design & Setup

Select and provision your modern data stack: ingestion, warehouse, transformation, BI — all infrastructure-as-code.

SPRINT 03

Build & Ship Dashboards

Migrate historical data, build pipelines and models, and deliver first executive dashboards within 4 weeks.

SPRINT 04

Enable & Govern

Self-serve onboarding, data dictionaries, governance, and ongoing support to make your team data-independent.

Case Study

D2C E-commerce — ₹140Cr revenue brand

Challenge

An established D2C cosmetics brand was running its weekly business review on 14 spreadsheets pulled by 4 analysts, with no real-time visibility into channel ROAS or customer lifetime value.

Solution

We built a Snowflake + dbt warehouse ingesting Shopify, Meta, Google Ads, Klaviyo, and Razorpay. A Looker semantic layer powers executive dashboards, and our team trained their finance and marketing leads on self-serve analytics.

Result

Weekly business review compressed from 2 days to 30 minutes. Reallocated ad spend based on real LTV-to-CAC data, lifting blended ROAS by 41% and contribution margin by 7 points in 6 months.

Let's talk about data analytics & business intelligence

Free 30-minute scoping call with a FalconX Tech practice lead. No pitch, just clarity on what's possible for your team.