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Making good use of data in schools – How can we best turn data into knowledge? — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Education Industry →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
disco.org.uk ↗	69 match 1 shared topics	Data in Schools Conference	United Kingdom en	education-industry WordPress	robotsllmsaihumans	emailphone	none
edudatapro.com ↗	66 match 1 shared topics	Education Data Protection – Practical, sensible advice and support for schools around data protection and GDPR compliance.	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
mindseyes.org ↗	66 match 1 shared topics	Home - Endeavor Schools	en	education-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	partial · 8
djm-teach.co.uk ↗	65 match 1 shared topics	Teaching in London schools in the UK \| DJM Personnel	United Kingdom en	education-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	none
assessortech.com ↗	65 match 1 shared topics	Assessor Tech – For Schools	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
digitalschools.eu ↗	65 match 1 shared topics	Home - Digital Schools Contest	European Union en	education-industry WordPress	robotsllmsaihumans	emailphone	none
shalapro.com ↗	65 match 1 shared topics	ShalaPro \| Best School Management Software in Rajasthan (RBSE)	en	education-industry WordPress	robots llmsaihumans	emailphone	none
astra-alliance.com ↗	65 match 1 shared topics	Astra SCITT \| School Centred Teacher Training in Buckinghamshire and beyond	en	education-industry	robotsllmsaihumans	emailphone	partial · 5
nurseconsultantassociates.com ↗	65 match 1 shared topics	Nurse Consultant Associates – We help nursing schools with curriculum development and national accreditation preparation	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
eduvisionanalytics.com ↗	65 match 1 shared topics	School Data Analytics Services \| EduVision Analytics	en	education-industry	robots llmsaihumans	emailphone	none
hadasyehez.com ↗	65 match 1 shared topics	Helping Founders and Schools Turn Ideas into Real Classroom Impact	en	education-industry	robotsllmsaihumans	emailphone	none
huddlestorm.com ↗	64 match 1 shared topics	DesignCase \| Thinking-First Innovation for Schools	United States~ en	education-industry Spree Commerce	robotsllmsaihumans	emailphone	none
8degreesup.com ↗	64 match 1 shared topics	Eight Degrees Up \| Human-First AI Consulting for Schools	en	education-industry Wix	robots llmsaihumans	emailphone	none
hallguardian.com ↗	64 match 1 shared topics	SmartTrack - School Attendance & Movement Tracking	en	education-industry	robotsllmsaihumans	emailphone	none
designtechnology.org.uk ↗	64 match 1 shared topics	We support and champion design and technology education in schools - D&T Association	United Kingdom en	education-industry	robotsllmsaihumans	emailphone	none
casbo.org ↗	64 match 1 shared topics	Home - California Association of School Business Officials	en	education-industry WordPress	robots llmsaihumans	emailphone	none
ccetschools.com ↗	64 match 1 shared topics	CCET SCHOOLS \| Africa's Premier School Management & Result System	Nigeria~ en	education-industry	robotsllmsaihumans	emailphone	none
kingtoneducation.com ↗	64 match 1 shared topics	Kington Education — Bringing the best of EdTech to UK schools	en	education-industry WordPress	robotsllmsaihumans	emailphone	none

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:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

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.