Download this white paper to learn:
- Advantages and use cases of machine learning (ML) across industries
- Training and deployment of ML models using StreamAnalytix
- Model management using StreamAnalytix
- How to operationalize models using StreamAnalytix
Enterprises use ML for its advantages like high-speed data processing, real-time insights, consistent decision-making, reusability, and extensibility across use cases like:
FINTECH
Fraud prevention
Risk management
Insider threats
Claim settlement
Customer acquisition
MANUFACTURING
Predictive maintenance
Tool life
Optimizing operations
Demand forecasting
Product development
AIRLINES
Dynamic pricing
Flight traffic
Price errors
Fuel efficiency
Flight search analysis
RETAIL
Recommendation
Price optimization
Sentiment analysis
Frauds
Data quality
HEALTHCARE
Personalized medicines
Document processing
Equipment maintenance
Drug delivery optimization
Occupancy estimation
MARKETING
Next best offer
Customer churn
Loyalty program performance
Content personalization
Social media analysis
This paper details how you can build, train, test, score, manage, and operationalize ML models using StreamAnalytix – a self-service ETL and analytics tool. The platform helps enterprises create batch and streaming ETL pipelines using drag-and-drop operators on a visual IDE. It has a wide array of built-in operators for data sources, transformations, ML, and data sinks.
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Ensure successful data ingestion on the cloud: Strategies for 2021
Mar 19, 2021 | 11:00 am PT / 2:00 pm ET
