Remove Duplicates from Streaming Content and Catalog Data
✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-12
Streaming platforms ingest content metadata from studios, distributors, aggregators, and internal editorial teams. The same title appears multiple times when different distributors deliver the same film with conflicting metadata, when a series is available in both standard and 4K versions tracked as separate entries, or when content re-licensed from another platform retains its old catalog entry. A movie listed as both 'The Dark Knight (2008)' and 'Dark Knight, The' from two different content feeds creates catalog confusion. dataclean.to matches streaming content by title, release year, runtime, and content provider to eliminate redundant catalog entries.
The Problem
Duplicate content records in streaming data degrade the user experience and complicate rights management. A subscriber searching for a specific movie finds it listed twice with different ratings or descriptions, creating uncertainty about which to watch. Play history is split between duplicate entries, breaking recommendation algorithms that rely on complete viewing data. Content licensing teams cannot accurately report catalog size to investors or regulators when duplicates inflate the count. Royalty calculations become unreliable when streams are distributed across duplicate entries for the same title. Recommendation engines trained on fragmented viewing data produce less relevant suggestions, reducing engagement. EIDR Entertainment Identifier Registry
How to Fix It
1
Export content catalog data
Pull content records from your catalog management system, content delivery feeds, and editorial databases into CSV format. Include title, release year, content type (movie/series/episode), runtime, genre, content provider, and any unique content IDs like EIDR.
2
Upload to dataclean.to
Upload the CSV. The tool compares titles, release years, runtimes, and content providers to identify entries that represent the same content from different metadata sources.
3
Review duplicate content clusters
Examine flagged groups. Common duplicates include the same movie from two distributors with different title formatting, standard and premium format versions tracked as separate titles, and re-licensed content that was not merged with the existing catalog entry.
4
Merge into canonical content records
Consolidate confirmed duplicates into single catalog entries. Retain the most complete metadata, link all available format versions (SD, HD, 4K) under one title, preserve all content provider IDs as cross-references, and keep the highest-quality description.
5
Export the clean content catalog
Download the deduplicated catalog for import into your streaming platform. Clean records ensure subscribers see one listing per title, recommendation engines work with complete viewing data, and rights reporting reflects actual catalog size.
Frequently Asked Questions
How does the tool handle different quality versions of the same content?
SD, HD, and 4K versions of the same title are flagged as related entries sharing the same base content. You can merge them into one catalog entry with format options listed, or keep them separate if your platform requires distinct entries per quality tier.
Can it match content across different title formatting conventions?
Yes. The tool normalizes title formatting by handling 'The' prefixes, year suffixes, and punctuation differences. 'The Dark Knight (2008)' and 'Dark Knight, The' are recognized as the same title.
What about series with individually licensed seasons?
When different seasons of the same series are licensed from different providers, they may have separate catalog entries. The tool flags entries sharing the same series title for review so you can link them under a single series record.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.