Clean your massive datasets automatically with Swiftask
Swiftask integrates with Big Data Cloud to automate the cleaning, normalization, and preparation of your large-scale data.
Result:
Save hundreds of hours on data preparation. Turn raw data into actionable insights instantly.
AI Agents
big data cloud
Connector big data cloud · Secure OAuth 2.0
Massive dataset cleaning is a bottleneck
Processing terabytes of raw data manually or through complex scripts is expensive and error-prone. Data teams spend 80% of their time cleaning rather than analyzing.
Main negative impacts:
Wasted storage and processing costs
Corrupted or duplicate data consumes valuable resources in Big Data Cloud.
Delays in AI projects
AI model quality depends directly on the cleanliness of training data.
Recurrent human errors
Manual or semi-automated cleaning introduces biases and inconsistencies.
Swiftask orchestrates the cleaning of your datasets in Big Data Cloud using specialized AI agents. Define your transformation rules and let Swiftask handle the massive volumes.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
Engineers write complex ETL scripts. Every format change requires rewriting. Processing takes days and requires constant human supervision to handle exceptions.
With Swiftask + Big Data Cloud
You configure a Swiftask agent with your business rules. It automatically scans, cleans, and normalizes your datasets in Big Data Cloud. The process is scalable, documented, and self-adjusting.
4 steps to automate your dataset cleaning
1
STEP 1 : Configure access to Big Data Cloud
Connect Swiftask to your Big Data Cloud instance via secure authentication.
2
STEP 2 : Define cleaning rules
Use natural language to instruct the agent on rules: duplicate removal, date formatting, missing value handling.
3
STEP 3 : Launch the processing pipeline
Activate the agent to start cleaning your target buckets or tables.
4
STEP 4 : Monitor and validate
Review the quality reports generated automatically after each execution.
AI processing capabilities
The agent analyzes statistical distribution, detects anomalies, and applies contextual transformations.
- Target connector: The agent performs the right actions in big data cloud based on event context.
- Automated actions: Intelligent deduplication, format normalization, missing value imputation, outlier filtering, type conversion.
- Native governance: Full traceability of every transformation for your compliance audits (GDPR/Data Governance).
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-big-data-cloud@swiftask.ai ). You keep full visibility on every action and every sent message.
Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.
Why choose Swiftask for your data
Native scalability
Process massive volumes without impacting system performance.
Consistent quality
Eliminate human bias with deterministic and documented AI rules.
Productivity gains
Free your Data engineers from repetitive cleaning tasks.
Guaranteed compliance
Every action is tracked and audited in the Swiftask interface.
Security and governance
Swiftask applies enterprise-grade security standards for your big data cloud automations.
- End-to-end encryption: Your data remains protected between Swiftask and Big Data Cloud.
- Full audit trail: Detailed history of all modifications made to datasets.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Operational impact
| Metric | Before | After |
|---|---|---|
| Preparation time | Full days | Minutes (automated processing) |
| Data accuracy | Frequent inconsistencies | 99.9% standardization |
Take action with big data cloud
Save hundreds of hours on data preparation. Turn raw data into actionable insights instantly.