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Sample Output

Research Database Cleanup & Enrichment

Preview of a real data enrichment deliverable. Below you can see the raw input data alongside our cleaned, standardized, and enriched output.

1,089
Records Delivered
19
Fields Per Record
39
Organizations
94%
Coverage Rate

Before: Raw Input Data

This is what the client's original data looked like — inconsistent formatting, missing fields, duplicate entries, and unstandardized values.

! Missing Fields

38% of records had no organization listed. 52% had no publication count or h-index. URLs were missing in 61% of rows.

~ Inconsistent Formatting

Names in mixed formats (First Last, Last First, all-caps). Locations listed as cities, countries, or abbreviations interchangeably.

# Duplicates & Errors

47 duplicate records found (4.3% of total). 23 records had wrong organization assignments. 15 had outdated titles.

Raw Input — 5 sample rows
Name Title Organization Location Expertise Pubs Scholar LinkedIn
CHEN, Sarah ML research scientist deepmind London UK — — — —
James Okonkwo sr. research eng — SF NLP, LLM — — linkedin.com/in/jokonkwo
Dr. Mei Zhang Research Director Alibaba DAMO Hangzhou Computer Vision 89 — —
Zhang, Mei Research Dir. Alibaba HZ, China CV — — —
Priya Ramaswamy — Meta FAIR NY — 42 scholar.google.com/citations?user=abc123 —
↓ AI Cleanup & Enrichment Pipeline ↓

After: Cleaned & Enriched Output

Every record standardized, de-duplicated, and enriched with public-source data. Consistent formatting across all 19 fields.

Enriched Output — 10 sample rows
Name Title Organization Location Expertise Pubs H-Index Scholar LinkedIn GitHub Status
Dr. Sarah Chen ML Research Scientist DeepMind London, UK Reinforcement Learning, Multi-Agent Systems 67 28 scholar/schen in/sarah-chen-ml gh/schen-rl Active
James Okonkwo Senior Research Engineer OpenAI San Francisco, CA NLP, Large Language Models, Alignment 34 18 scholar/jokonkwo in/jokonkwo gh/jokonkwo Active
Dr. Mei Zhang Research Director Alibaba DAMO Academy Hangzhou, China Computer Vision, Object Detection, 3D Reconstruction 89 35 scholar/mzhang in/mei-zhang-cv — Active
Priya Ramaswamy Research Scientist Meta FAIR New York, NY Self-Supervised Learning, Vision Transformers 42 22 scholar/pramaswamy in/priya-r-ml gh/priya-ssl Active
Dr. Alex Petrov Principal Scientist Anthropic San Francisco, CA AI Safety, Constitutional AI, RLHF 51 26 scholar/apetrov in/alex-petrov-ai gh/apetrov Active
Yuki Tanaka Staff Research Engineer Google Brain Mountain View, CA Distributed Training, Model Parallelism 28 15 scholar/ytanaka in/yuki-tanaka gh/ytanaka-ml Active
Dr. Fatima Al-Rashid Assistant Professor Stanford University Stanford, CA Robotics, Embodied AI, Sim-to-Real Transfer 73 31 scholar/falrashid in/fatima-alrashid gh/falrashid Active
Marcus Williams Research Scientist NVIDIA Research Santa Clara, CA GPU Computing, Neural Rendering, NeRF 56 24 scholar/mwilliams in/marcus-w-nvidia gh/mwilliams Active
Dr. Lin Wei Senior Research Scientist Tencent AI Lab Shenzhen, China Speech Synthesis, Audio Generation, TTS 45 20 scholar/lwei in/lin-wei-ai — Active
Elena Voronova Former Research Lead DeepSeek Beijing, China Code Generation, Program Synthesis 38 19 scholar/evoronova in/elena-voronova gh/evoronova Moved

Data Quality Report

Coverage rates for each enriched field across the full 1,089-record dataset.

Full Name
100%
Title / Role
98%
Organization
97%
Location
95%
Expertise Areas
96%
Publications Count
91%
H-Index
88%
Google Scholar URL
89%
LinkedIn URL
92%
GitHub URL
74%
X / Twitter URL
68%
Status (Active/Moved)
100%

All 19 Enriched Fields

Every record in the delivered CSV contains these standardized fields.

1 Full Name
2 Title / Role
3 Organization
4 Department
5 Location (City)
6 Location (Country)
7 Expertise Areas
8 Research Focus
9 Education
10 Publications Count
11 H-Index
12 Google Scholar URL
13 LinkedIn URL
14 GitHub URL
15 X / Twitter URL
16 Personal Website
17 Bio Summary
18 Status
19 Last Verified

What We Fixed

Summary of data quality issues identified and resolved during the cleanup process.

Issue Records Affected % of Total Resolution
Duplicate records 47 4.3% Merged & de-duplicated (kept richest record)
Missing organization 414 38.0% Enriched from LinkedIn & Scholar profiles
Inconsistent name format 289 26.5% Standardized to “First Last” with Dr. prefix where applicable
Missing publication data 567 52.1% Scraped from Google Scholar & Semantic Scholar
No profile URLs 665 61.1% Discovered via public search (Scholar, LinkedIn, GitHub)
Wrong org assignment 23 2.1% Cross-referenced with latest public profiles
Outdated job title 15 1.4% Updated from current LinkedIn profiles
Location inconsistencies 312 28.7% Standardized to “City, Country” format

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