Da Nang data test environment · DADEP Sandbox

Evaluate real data before you decide to buy

Explore a secure Sandbox built to VIFC standards and Data Law 60/2024. Query, analyze and visualize sample data right in your browser inside a fully isolated container — no installation needed.

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Decree 13/2023 · PII masking
Dedicated RAM & CPU partitions
100% de-identified

Isolated Sandbox · VM container

Sandbox Active

In [1]Python 3.10 · 4 GB RAM

1import pandas as pd
2# Load the Da Nang retail sample data package (PII removed)
3df = pd.read_csv('retail_danang_sample.csv')
4df[['id', 'customer', 'district', 'revenue']].head(4)

Out [1]3 / 500,000 records

Data preview · sensitive fields are masked

ID	Customer (masked)	Area	Revenue	Status
DN-99201	*** NGUYEN V. A	Hải Châu	145,500,000 ₫	✓ Verified
DN-99202	*** TRAN THI B	Sơn Trà	280,000,000 ₫	✓ Verified
DN-99203	*** LE HOANG C	Ngũ Hành Sơn	92,300,000 ₫	✓ Verified

Illustration of the Workspace interfaceTrial quota: 100% free

Appraisal & evaluation

DADEP Sandbox data testing capabilities

Comprehensive, fully transparent analysis before you proceed to a commercial transaction or an auction.

01
Sample data preview & data masking
Explore the real schema and public sample tables with 100% PII masking to guarantee legal compliance before bidding opens.
- Assess the missing / complete ratio of the dataset
- Automatic encryption of sensitive fields under Decree 13/2023
- Review the schema against National Data Portal standards
Live masking engine
Masked
Identifier Personal name Segment
ID-90812 *** NGUYEN V. A Retail consumer
ID-90813 *** TRAN THI B Mid-size enterprise
ID-90814 *** LE HOANG C Consumer finance
Complies with Decree 13/2023/ND-CP on personal data protection
02
Live SQL/Python programming & queries
A smooth in-browser code environment supporting popular data-science libraries (Pandas, NumPy, Scikit-learn) with syntax hints and low-latency virtual-machine execution.
- Python 3.10, R and an ANSI-standard SQL engine side by side
- Run analysis algorithms with a response time under 0.2 seconds
- Smart source-code suggestions (IntelliSense auto-complete)
Live query
Exec: 0.12s
```
SELECT * FROM retail_sample
WHERE district = 'Hải Châu' LIMIT 50;
```
Query status: OK (200)Rows: 42,000 matches
03
Chart visualization & report export
Turn raw data into strategic insight with interactive charting tools. Export the evaluation result as a professional PDF report in one click.
- Integrated Matplotlib, Seaborn & interactive Plotly
- Charts with tooltips that inspect every data point
- Generate a quality-evaluation report in one click
Dynamic chart
Da Nang: 210 million VND (up 18%)
Data reliability: 98.6%
Export PDF report
04
Resource control & isolated container
Each trial session runs on a fully isolated virtual workspace. CPU, RAM and session lifetime are controlled automatically so no raw data leaks to the outside.
- 4 GB RAM & 2 dedicated vCPUs per evaluating organization
- Sessions end automatically when idle to save resources
- Free Internet egress blocked; results leave only through automatic review
Live resource gauge
Active
RAM (live)2.1 GB / 4.0 GB (52%)
CPU load12% (normal)
Session uptime: 45:00Isolated box guard active

Identifier	Personal name	Segment
ID-90812	*** NGUYEN V. A	Retail consumer
ID-90813	*** TRAN THI B	Mid-size enterprise
ID-90814	*** LE HOANG C	Consumer finance

Ready to test and evaluate data?

Request a dedicated Sandbox environment to trial algorithms and check data quality before you submit an auction file or buy a license.

Browse the data product catalogue

Evaluate real data before you decide to buy

DADEP Sandbox data testing capabilities

Sample data preview & data masking

Live SQL/Python programming & queries

Chart visualization & report export

Resource control & isolated container

Ready to test and evaluate data?