Data Engineering & Analytics Services

Computer Kingdom builds the data infrastructure that lets your business answer real questions instead of arguing about which spreadsheet has the right number. Modern data warehouses, ETL / ELT pipelines, BI dashboards, and self-service analytics — designed to fit a 50-200 person Indian business, not a Fortune 500.

The pattern we see most often: data lives in 5-10 different systems (CRM, accounting, operations, e-commerce, payroll), nobody can produce a unified view of revenue or customer lifetime value, and the leadership team makes decisions on stale month-end PDFs. We fix that with a data warehouse, scheduled extracts from each system, a single semantic layer, and dashboards that update hourly. Most projects show a single trustworthy revenue number on screen within 30 days.

What We Build

Common engagements include:

Data Project Process

We start with one well-defined business question. The infrastructure follows from that.

1. Question selection — you tell us what decision the data needs to support. "How is the business performing?" is too vague; "which channels deliver customers with 12-month repeat-purchase rates above 40%" is buildable.
2. Source-system audit — where does the data live, who owns it, what's the API or export path, what's the historical depth?
3. Warehouse & pipeline build — data flows from source systems into the warehouse on a schedule with documented transformations.
4. Semantic layer — business terms get one definition ("active customer" means X) so dashboards can never disagree.
5. Dashboards & access — the question gets answered. Then you and your team start asking new questions on the same foundation.
6. Maintenance & iteration — data engineering is never done; we run a monthly check-in to add new sources, retire stale dashboards, and fix what's drifted.

Data Stack

Modern data engineering uses a relatively small set of well-understood tools. We standardise on these.

• Data warehouses: PostgreSQL, ClickHouse, Snowflake, BigQuery, Amazon Redshift, Microsoft Fabric
• Transformation: dbt (the standard for SQL-based transformation), Apache Spark for large-data engineering
• Orchestration: Apache Airflow, Dagster, Prefect, AWS Step Functions for serverless workflows
• Ingestion: Fivetran, Airbyte, custom Python connectors for niche systems
• BI & visualisation: Metabase (favourite for SMEs), Looker, Power BI, Apache Superset, Tableau
• Streaming & CDC: Debezium for change-data-capture, Apache Kafka, Redpanda
• Notebook & ad-hoc analysis: JupyterLab, Hex, DataGrip, Mode
• Data quality: dbt tests, Great Expectations, Soda, Monte Carlo for data observability at scale

Why Choose Computer Kingdom

• 25+ years of track record. We have been delivering custom IT work in Pune since 1999.
• Local Pune presence. Our team is based at M.G. Road, Camp — in-person meetings and local support are easy.
• End-to-end delivery. We cover discovery, design, build, QA, deployment, and support under one roof.
• Pragmatic technology choices. We pick tools that match your team’s capacity to maintain the system long-term.
• Honest communication. You get direct access to the people doing the work. If something is slipping, you hear it from us early.

Frequently Asked Questions

How much does a data warehouse project cost?

A focused first build — one warehouse, 3-5 source systems, one semantic layer, one core dashboard set — ranges ₹8L-₹20L. A larger build covering full Customer 360 with operational dashboards across departments ranges ₹20L-₹60L+. Ongoing maintenance and new-question delivery is usually ₹50K-₹2L per month.

Which data warehouse should we pick?

If your data fits in PostgreSQL (under ~500GB) and your queries aren't extreme, plain Postgres is fine and cheap. ClickHouse for analytics-heavy workloads under 10TB. BigQuery if you're already on GCP or doing serious ML. Snowflake for enterprise scenarios with complex governance. We'll recommend based on actual data volume, not vendor preference.

How long until we see our first dashboard?

First dashboard answering the first business question: typically 4-6 weeks from project start. That's intentional — we want value visible early so the project has internal momentum, rather than disappearing into a 6-month "we're still building infrastructure" phase.

Can you connect to Tally / Zoho Books / SAP / our CRM?

Yes. Tally has APIs (and we've built custom extractors for older versions). Zoho, Salesforce, HubSpot, Microsoft Dynamics — all standard via Fivetran or Airbyte connectors. SAP requires more work but we've done it. We've extracted data from systems that don't have APIs at all using scheduled SQL queries against the underlying database.

Do we need a data scientist or just a data engineer?

Most SMEs need data engineering and analytics first — reliable pipelines, clean dashboards, single source of truth. Data science (predictive modelling, ML) only pays off after that foundation exists. We focus on the engineering and analytics layer; we'll bring in or help you hire data science capabilities when the foundation is ready and there's a clear ROI question.

What about real-time analytics?

True real-time (sub-second) analytics is rarely needed and adds significant cost and complexity. Most "real-time" requirements are actually "near-real-time" (refreshed every 5-15 minutes), which is achievable with reasonable engineering. We push back on real-time when the business case isn't clear.

Can you train our team to maintain this themselves?

Yes — many of our engagements include knowledge-transfer phases where we hand over the warehouse, dbt models, and dashboards with documentation and training. We then drop to a smaller retainer for support and architectural reviews.

Start Your Project

Ready to discuss your requirements? Call +91 99609 03132, email rakesh@ecomputerkingdom.com, or send us a message. Initial consultations are free and no-obligation — we will give you an honest view of whether what you need is a good fit for us.