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Create and complete the following summary table batch processing?
zanele nokuthula
Apr 19
Create and complete the following summary table batch processing?
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ChatGPT
Apr 19
| Aspect | Description |
|---------------------|-----------------------------------------------------------------------------|
| Definition | Batch processing is a method of processing data in which a group of transactions is collected over a period of time and processed all at once. |
| Processing Speed | Batch processing is typically slower than real-time processing as data is collected and processed in batches rather than immediately. |
| Efficiency | Batch processing is efficient for handling large volumes of data as it allows for processing multiple transactions at once. |
| Cost | Batch processing is cost-effective as it reduces the need for constant monitoring and processing of individual transactions. |
| Examples | Examples of batch processing include payroll processing, billing systems, and end-of-day financial transactions. |
|---------------------|-----------------------------------------------------------------------------|
| Definition | Batch processing is a method of processing data in which a group of transactions is collected over a period of time and processed all at once. |
| Processing Speed | Batch processing is typically slower than real-time processing as data is collected and processed in batches rather than immediately. |
| Efficiency | Batch processing is efficient for handling large volumes of data as it allows for processing multiple transactions at once. |
| Cost | Batch processing is cost-effective as it reduces the need for constant monitoring and processing of individual transactions. |
| Examples | Examples of batch processing include payroll processing, billing systems, and end-of-day financial transactions. |
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Google Gemini AI
Apr 19
| Attribute | Batch Processing |
|---|---|
| Definition | A processing technique that groups similar tasks or operations together and processes them as a single batch. |
| Batch Size | Determines the number of tasks or operations included in a batch. |
| Processing Mode | Can be either offline (asynchronous) or nearline (synchronous). |
| Input | Typically involves large volumes of structured or unstructured data. |
| Output | Results are usually produced in a consolidated or aggregated form. |
| Execution | Often scheduled or triggered based on specific criteria or time intervals. |
| Advantages |
| - Improved resource utilization
| - Cost efficiency
| - Increased parallelism and scalability
| - Reduced latency for real-time processing
| Disadvantages |
| - May not be suitable for time-sensitive or interactive workloads
| - Can result in data latency depending on batch size and processing schedule
| Applications |
| - Data warehousing and analytics
| - Data cleansing and transformation
| - Machine learning and artificial intelligence (AI) training
| - ETL (extract, transform, load) processes
| Examples |
| - Hadoop
| - Spark
| - Flink
| - AWS Batch
|---|---|
| Definition | A processing technique that groups similar tasks or operations together and processes them as a single batch. |
| Batch Size | Determines the number of tasks or operations included in a batch. |
| Processing Mode | Can be either offline (asynchronous) or nearline (synchronous). |
| Input | Typically involves large volumes of structured or unstructured data. |
| Output | Results are usually produced in a consolidated or aggregated form. |
| Execution | Often scheduled or triggered based on specific criteria or time intervals. |
| Advantages |
| - Improved resource utilization
| - Cost efficiency
| - Increased parallelism and scalability
| - Reduced latency for real-time processing
| Disadvantages |
| - May not be suitable for time-sensitive or interactive workloads
| - Can result in data latency depending on batch size and processing schedule
| Applications |
| - Data warehousing and analytics
| - Data cleansing and transformation
| - Machine learning and artificial intelligence (AI) training
| - ETL (extract, transform, load) processes
| Examples |
| - Hadoop
| - Spark
| - Flink
| - AWS Batch
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