Question 1

We already have data in spreadsheets — is that enough?

Accepted Answer

For very early-stage businesses, yes. But as you scale, spreadsheets break down: they can't handle multiple data sources reliably, they're error-prone, and they can't give real-time visibility. A proper data stack centralizes everything and makes your data trustworthy and fast to query.

Question 2

Which data warehouse do you recommend?

Accepted Answer

Snowflake for most mid-market companies — it's flexible, scales automatically, and has excellent tooling support. BigQuery if you're already invested in Google Cloud. Redshift if you're AWS-native. We'll give a concrete recommendation after understanding your data volume and query patterns.

Question 3

How do you ensure data quality?

Accepted Answer

We implement dbt tests for schema and value validation, set up Airflow alerts on pipeline failures, and build data quality dashboards so issues are visible before they affect downstream reports. Data quality is engineered in, not inspected after the fact.

Question 4

Can you work with our existing BI tool (Tableau, Power BI)?

Accepted Answer

Yes — we build the clean, reliable data layer underneath and let you keep the BI tool your team already knows. We connect to Tableau, Power BI, Metabase, Looker, Superset, and most others via standard SQL connectors.

Data Engineering & Analytics

Everything you get

Tools & Technologies We Use

Recent Work

Brenda Levy Guiffrida — Houston Realtor

AZ Interiors — Upholstered Furniture Store

Koncept — Renovation & Interior Design

Common Questions

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