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BI, Analytics & Dashboards

Turn scattered data into clear, live dashboards and trusted insight that supports better decisions.

[ OVERVIEW ]

Based in Pune, India, we build the full path from raw data to a decision: audited sources, a reliable ingestion and transformation layer, a modelled warehouse you can trust, and dashboards that answer the questions leadership actually asks. One number, one meaning, everywhere it appears.

Governance is built in from day one — definitions, lineage and access policies — so the numbers stay consistent as the business, and the data behind it, keep growing.

[ DATA_PIPELINE ]

SEQUENCE · 6 STAGES
01Data auditMap every source and what it can, and can't, be trusted for.
02Ingestion & ETLReliable, scheduled pipelines from source to warehouse.
03Warehouse modellingA clean model that answers questions consistently.
04Metric governanceOne definition per metric, versioned and owned.
05Dashboard designLive views tuned to the decisions they support.
06Ongoing optimisationMonitored and extended as the business changes.

[ CAPABILITIES ]

5 AREAS OF WORK
01 Data audit

Map every source and assess what each can, and can't, be trusted for.

02 Pipeline & ETL

Reliable ingestion and transformation — scheduled, monitored and idempotent.

03 Warehouse modelling

A clean, tested data model that answers questions consistently across the business.

04 Executive dashboards

Live views tuned to the decisions they support, not the data they happen to contain.

05 Governance

Definitions, lineage, access policies and change control kept in order.

[ STACK ]

TOOLING
Python SQL dbt BigQuery Snowflake Looker Power BI Apache Airflow Fivetran

[ EXAMPLE_OUTCOME ]

ILLUSTRATIVE
[ SCENARIO ]

Sales, inventory, profit and branch performance lived in four disconnected systems — leadership now reads them from one live dashboard, with a single definition for every metric.

ILLUSTRATIVE ENGAGEMENT
0
SOURCE OF TRUTH

Frequently Asked Questions

How do you design a dashboard that leadership will actually use?

We start from the decisions the dashboard needs to support, not the data that happens to exist. Each view is tuned to those decisions, with one definition per metric so the same number means the same thing everywhere it appears.

What is an ETL pipeline and why does my business need one?

ETL pipelines extract data from your source systems, transform it into a consistent shape, and load it into a warehouse on a schedule. Without one, every report re-derives its own numbers by hand — which is where dashboards start to disagree.

Do I need a data warehouse if I already have a database?

A production database is built for transactions, not analysis — heavy reporting queries slow it down. A warehouse holds a modelled, query-optimised copy of your data, so reporting never competes with the app it's fed from.

Real-time or batch reporting — which do I need?

Batch (hourly or daily refresh) covers most business reporting and costs far less to run. We recommend real-time only for operational dashboards where a same-minute decision genuinely depends on it.

How do you choose between Power BI, Looker and other BI tools?

It comes down to your existing stack, budget and who's building reports day to day — Power BI fits Microsoft-centric teams well, Looker suits teams already on Google Cloud. We build the warehouse layer to work with whichever tool you pick.