Intelligent data cleaning for your Keboola pipelines
Swiftask integrates with Keboola to automate the cleaning and normalization of your datasets. Free your engineers from repetitive preparation tasks.
Result:
Ensure the reliability of your decision-making data with automated, consistent preparation.
AI Agents
keboola
Connector keboola · Secure OAuth 2.0
Manual data prep slows down your projects
Keboola pipelines are powerful, but input data quality remains a challenge. Teams spend 80% of their time fixing formats, handling missing values, or harmonizing disparate sources.
Main negative impacts:
ETL bottlenecks
Manual cleaning creates endless queues, delaying the availability of data for analysts.
Normalization errors
Hard-coded cleaning scripts are fragile. A source change can corrupt your entire pipeline.
High operational costs
Using data engineers for basic cleaning tasks is a waste of strategic resources.
Swiftask acts as an intelligence layer on your Keboola flows. Our AI agents analyze and clean your data in real-time, based on business rules you define without coding.
BEFORE / AFTER
What changes with Swiftask
Traditional cleaning process
A data engineer writes complex Python scripts in Keboola to handle format errors. As soon as a new source arrives, they must manually edit the code, test, and redeploy.
Cleaning assisted by Swiftask
Your Swiftask AI agent automatically detects anomalies in your Keboola buckets. It applies corrections, normalizes formats, and flags complex cases, all autonomously.
Optimize your Keboola flows in 4 steps
1
STEP 1 : Connect Swiftask to Keboola
Use Keboola API tokens to allow Swiftask to read and write to your data buckets securely.
2
STEP 2 : Define your cleaning rules
Express your needs in plain language: date normalization, duplicate removal, enrichment of missing fields.
3
STEP 3 : Trigger the agent on your pipelines
Integrate the agent into your Keboola workflow. It intervenes after extraction to prepare data before loading.
4
STEP 4 : Monitor quality
Access the Swiftask dashboard to validate corrections and adjust the agent's directives in real-time.
Intelligent cleaning capabilities
The agent examines the structure, completeness, and semantic consistency of your raw data in Keboola.
- Target connector: The agent performs the right actions in keboola based on event context.
- Automated actions: Detection and removal of complex duplicates. Format harmonization (dates, currencies, units). Intelligent imputation of missing values based on history. Cross-validation between different data sources.
- Native governance: All transformations are documented and auditable, ensuring total transparency on your data lineage.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-keboola@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.
Business efficiency gains
Agile data engineering
Reduce the development time for your data transformations from days to minutes.
Constant data quality
Eliminate human errors through rigorous, automated execution of cleaning rules.
Cost reduction
Free up your technical talent for high-value data architecture projects.
Effortless scalability
Process growing volumes of data without increasing your manual workload.
Decision confidence
Make decisions based on clean data, validated and normalized by a reliable AI.
Data security and governance
Swiftask applies enterprise-grade security standards for your keboola automations.
- Secure API integration: The connection to Keboola complies with strict security standards, ensuring your dataset integrity.
- Guaranteed privacy: Your data is processed in accordance with GDPR standards and your internal protection policies.
- Transformation traceability: Every cleaning operation is logged, allowing for a full rollback if needed.
- Granular access control: Precisely define which collaborators can configure cleaning rules within your Keboola projects.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your data operations
| Metric | Before | After |
|---|---|---|
| Preparation time | 80% of project time | Less than 20% (supervision) |
| Data error rate | High (manual) | Near zero |
| Pipeline velocity | Slow sequential process | Continuous, automated flow |
| Technical maintenance | Fragile scripts (time-consuming) | No-code rules (agile) |
Take action with keboola
Ensure the reliability of your decision-making data with automated, consistent preparation.