Tarification

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.

Resultat:

Save hundreds of hours on data preparation. Turn raw data into actionable insights instantly.

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.

Les principaux impacts négatifs :

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.

AVANT / APRÈS

Ce qui change avec 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

ÉTAPE 1 : Configure access to Big Data Cloud

Connect Swiftask to your Big Data Cloud instance via secure authentication.

ÉTAPE 2 : Define cleaning rules

Use natural language to instruct the agent on rules: duplicate removal, date formatting, missing value handling.

ÉTAPE 3 : Launch the processing pipeline

Activate the agent to start cleaning your target buckets or tables.

ÉTAPE 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.

Connecteur cible : L'agent exécute les bonnes actions dans big data cloud selon le contexte de l'événement.
Actions automatisées : Intelligent deduplication, format normalization, missing value imputation, outlier filtering, type conversion.
Gouvernance native : Full traceability of every transformation for your compliance audits (GDPR/Data Governance).

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-big-data-cloud@swiftask.ai ). Vous gardez une visibilité complète sur chaque action et chaque message envoyé.

À retenir : L'agent automatise les décisions répétitives et laisse à vos équipes les actions à forte valeur.

Why choose Swiftask for your data

1. Native scalability

Process massive volumes without impacting system performance.

2. Consistent quality

Eliminate human bias with deterministic and documented AI rules.

3. Productivity gains

Free your Data engineers from repetitive cleaning tasks.

4. Guaranteed compliance

Every action is tracked and audited in the Swiftask interface.

Security and governance

Swiftask applique des standards de sécurité enterprise pour vos automatisations big data cloud.

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.

Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.

RÉSULTATS

Operational impact

Métrique	Avant	Après
Preparation time	Full days	Minutes (automated processing)
Data accuracy	Frequent inconsistencies	99.9% standardization

Passez à l'action avec big data cloud

Save hundreds of hours on data preparation. Turn raw data into actionable insights instantly.

Analyse prédictive continue : exploitez vos données Big Data Cloud avec Swiftask

Cas d'usage suivant.