The workflow before#
The firm's deal data lived in Salesforce, the portfolio system, finance systems, PitchBook, Crunchbase, news feeds and shared spreadsheets, each with its own naming. Analysts spent about 70% of their time collecting and reconciling data by hand. A CIM review took about 4 weeks, and a full company profile took days to assemble.
What we built#
We built a governed data layer that pulls 15+ internal and external sources into Snowflake on AWS. Meltano extracts each source on schedule, raw files land in S3, and Snowpipe loads them into bronze, silver and gold layers.
dbt holds the business logic in 200+ tested models (500+ data tests), Airflow runs 50+ pipelines, and Looker gives deal teams self-service dashboards for pipeline status, portfolio metrics and benchmarks.
Deal teams now open a CIM review with the company, market and comparable data already assembled, so review time goes to judgment instead of collection.
Before and after#
| Measure | Before | After |
|---|---|---|
| CIM review cycle | 4 weeks | 1 week |
| Analyst time on manual data work | 70% | 15% |
| Analyst queue on data prep | 70 | 10 |
| Report generation | Days | Minutes |
What's next#
With every source unified and tested, the next step is an L3 agent that reads each incoming CIM, scores it against the firm's criteria and routes the strong ones to the deal team for review.
