Data you can trust in the Monday meeting
Pipelines that collect, clean and model your data, and dashboards that show one set of numbers everyone agrees on.
Capabilities
Pipelines and ETL
Scheduled jobs that extract, clean and load data, with alerts on failure.
Data collection
Scrapers and API connectors for prices, listings, maps and other external data.
Warehouses and modelling
Tables shaped around business questions, with tested transformations in dbt.
Dashboards and reports
Clear dashboards with written metric definitions.
Streaming and sync
Near real-time feeds where daily batches are too slow.
Data for AI
Documents and records prepared so assistants and models can use them safely.
Good fit if
- Different reports give different answers to the same question
- Someone spends hours each week merging spreadsheets
- You want data from websites, APIs or partners you do not collect yet
Typical use cases
What we use
- Processing
- PythonPandasSparkKafkaAirflowdbt
- Storage
- PostgreSQLBigQuerySnowflakeRedshiftMongoDB
- Collection
- ScrapySeleniumBeautifulSoupREST APIsWebhooks
- Reporting
- Power BITableauMetabaseLooker Studio
Four steps, in this order
- 01
List the questions
- 02
Map the sources
- 03
Build and test pipelines
- 04
Document the metrics
Related work
Profitory - True Net-Profit Analytics
Shows online stores what they actually keep: net profit and margin that fold in cost of goods, shipping, fees, ad spend, overheads, and refunds, down to a single order.
View case study →
Bullion Exchange Scraper
An automated scraper that collects precious metal prices and market data from bullion exchanges in real time.
View case study →
Map Data Scraper for Lead Generation
An automated scraper that pulls business listings from map services and turns them into clean lead lists.
View case study →
Traffic Monitoring System
A traffic monitoring system that tracks vehicle flow and congestion in real time.
View case study →Do we need a data warehouse?
Not always. If your data fits comfortably in PostgreSQL and a few people use the reports, a well modelled database and a dashboard tool may be enough. We recommend a warehouse such as BigQuery or Snowflake when data volume or the number of sources makes that worthwhile.
Can you collect data from websites?
Yes, where it is legally and contractually allowed. We build scrapers that respect site terms and rate limits, and we prefer official APIs when they exist.
Which dashboard tools do you use?
Power BI, Looker Studio, Metabase or Tableau, depending on what your team already pays for. We can also build reporting screens directly into your own product.
How do we start?
Book a call or send a message describing the problem. We follow up with questions, then send a written scope and estimate. Nothing is billed before you agree to that plan.
Tired of reconciling spreadsheets?
Tell us which reports you rely on. We will suggest a simple first pipeline.