Piperic
similar sites
‹ ProfileAI ReportTools

Sites similar to silviadata.dev

Silvia Arellano - Senior Data Architect & ETL Pipeline Engineer · ranked by shared content topics & relevance
73match
adithyapathipaka.dev
Adithya Pathipaka | Senior Data Platform Engineer
2 shared topicsdatabases
73match
ateeqrehman.com
Ateeq Ur Rehman | Senior Data Engineer – Snowflake, Spark, Kafka, dbt
2 shared topicsdatabases
70match
prismdatalabs.co.uk 🇬🇧
Prism Data Labs | Data Architecture as a Service
2 shared topicsdata-storage-and-warehousing
70match
lorisgjini.com
Loris Gjini | Data Engineer & Data Warehouse Consultant
2 shared topicsdatabases
68match
adrienledoux.dev
Adrien Ledoux | Data Platform Architect
2 shared topicsdata-storage-and-warehousing
67match
cabreradfall.dev
Abraham Cabrera | Data Architect Portfolio
2 shared topicsdatabases
66match
mrasyadc.com
Muhammad Rasyad Caesarardhi — Data Engineer
2 shared topicsdatabases
66match
crawlmine.com
CrawlMine — Data Extraction, Engineered
2 shared topicsdatabases
66match
buktoria.com
Home | Victoria Bukta - Data Lakehouse
2 shared topicsdata-storage-and-warehousing
66match
buktoria.io
Home | Victoria Bukta - Data Lakehouse
2 shared topicsdata-storage-and-warehousing
65match
dataturbine.co.uk 🇬🇧
Data Turbine
2 shared topicsdatabases
65match
holdpile.com
Holdpile - Simple data management
2 shared topicsdata-storage-and-warehousing
65match
datagile.co.uk 🇬🇧
Comprehensive Data Management & Solutions | Datagile
2 shared topicsdatabases
65match
credidatagroup.com
Credi Data Group — Your data, engineered.
2 shared topicsdata-storage-and-warehousing
65match
cosvaro.com
Cosvaro - Data Processing Made Simple
2 shared topicsdata-storage-and-warehousing
65match
thatfuse.com
Datafuse: Big Data Integration and Analytics Platform | DataFuse
2 shared topicsdatabases
65match
creanconsulting.com
Crean Consulting Inc for Data Warehousing SQL SERVER Oracle DB2 Informix Sybase Services
2 shared topicsdatabases
64match
data-visual.co.uk 🇬🇧
DataVisual | Cognos | Business Intelligence | Data Warehousing
2 shared topicsdatabases

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.