Data Processing Task
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A Data Processing Task is a processing task that can be used to create data processing systems (that transform raw data into processed information through data processing operations).
- AKA: DPT, Data Manipulation Task, Data Transformation Task, Data Handling Task.
- Context:
- It can typically transform Raw Data through data processing algorithms using data processing operations and data processing techniques.
- It can typically handle Data Processing Input through data processing ingestion, data processing validation, and data processing parsing.
- It can typically produce Data Processing Output through data processing transformation, data processing formatting, and data processing delivery.
- It can typically maintain Data Processing Quality through data processing integrity checks, data processing error handling, and data processing verification.
- It can typically optimize Data Processing Performance through data processing parallelization, data processing caching, and data processing resource management.
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- It can often utilize Data Processing Tools through data processing frameworks, data processing libraries, and data processing platforms.
- It can often implement Data Processing Patterns through data processing pipelines, data processing workflows, and data processing architectures.
- It can often ensure Data Processing Compliance through data processing governance, data processing audit trails, and data processing security measures.
- It can often enable Data Processing Automation through data processing scheduling, data processing orchestration, and data processing monitoring.
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- It can range from being a Small-Data Processing Task to being a Big-Data Processing Task, depending on its data processing volume scale.
- It can range from being a Batch Data Processing Task to being a Stream Data Processing Task, depending on its data processing temporal mode.
- It can range from being a Structured Data Processing Task to being an Unstructured Data Processing Task, depending on its data processing data format.
- It can range from being a Simple Data Processing Task to being a Complex Data Processing Task, depending on its data processing computational complexity.
- It can range from being a Manual Data Processing Task to being an Automated Data Processing Task, depending on its data processing automation level.
- It can range from being a Local Data Processing Task to being a Distributed Data Processing Task, depending on its data processing architecture scale.
- It can range from being a Real-Time Data Processing Task to being a Offline Data Processing Task, depending on its data processing latency requirement.
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- It can be solved by Data Processing Systems implementing data processing algorithms.
- It can be composed of Data Processing Subtasks including data processing acquisition, data processing transformation, and data processing storage.
- It can maintain Data Processing History for data processing tracking and data processing reproducibility.
- It can integrate with Data Processing Infrastructure through data processing interfaces and data processing protocols.
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- Example(s):
- Data Acquisition Processing Tasks, such as:
- Data Collection Processing Tasks (of gathering data processing tasks) demonstrating data processing source integration.
- Data Import Processing Tasks (of ingestion data processing tasks) demonstrating data processing format conversion.
- Data Entry Processing Tasks (of manual data processing tasks) demonstrating data processing human input.
- Data Extraction Processing Tasks (of retrieval data processing tasks) demonstrating data processing content isolation.
- Data Transformation Processing Tasks, such as:
- Data Cleaning Processing Tasks (of quality data processing tasks) demonstrating data processing error correction.
- Data Normalization Processing Tasks (of standardization data processing tasks) demonstrating data processing format unification.
- Data Aggregation Processing Tasks (of summarization data processing tasks) demonstrating data processing consolidation.
- Data Enrichment Processing Tasks (of enhancement data processing tasks) demonstrating data processing value addition.
- Extract-Transform-Load (ETL) Processing Tasks, such as:
- Database ETL Processing Tasks (of warehouse data processing tasks) demonstrating data processing pipeline execution.
- Real-Time ETL Processing Tasks (of streaming data processing tasks) demonstrating data processing continuous flow.
- Cloud ETL Processing Tasks (of distributed data processing tasks) demonstrating data processing scalable architecture.
- Signal Data Processing Tasks, such as:
- Audio Signal Processing Tasks (of sound data processing tasks) demonstrating data processing waveform manipulation.
- Image Signal Processing Tasks (of visual data processing tasks) demonstrating data processing pixel transformation.
- Sensor Signal Processing Tasks (of IoT data processing tasks) demonstrating data processing real-time filtering.
- Text Data Processing Tasks, such as:
- Natural Language Processing Tasks (of linguistic data processing tasks) demonstrating data processing semantic analysis.
- Document Processing Tasks (of content data processing tasks) demonstrating data processing structure extraction.
- Log Processing Tasks (of system data processing tasks) demonstrating data processing pattern detection.
- Scientific Data Processing Tasks, such as:
- Genomic Data Processing Tasks (of biological data processing tasks) demonstrating data processing sequence analysis.
- Climate Data Processing Tasks (of environmental data processing tasks) demonstrating data processing temporal aggregation.
- Particle Physics Data Processing Tasks (of experimental data processing tasks) demonstrating data processing event reconstruction.
- Business Data Processing Tasks, such as:
- Transaction Processing Tasks (of financial data processing tasks) demonstrating data processing consistency maintenance.
- Customer Data Processing Tasks (of CRM data processing tasks) demonstrating data processing profile management.
- Inventory Data Processing Tasks (of operational data processing tasks) demonstrating data processing stock tracking.
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- Data Acquisition Processing Tasks, such as:
- Counter-Example(s):
- Data Analysis Tasks, which focus on data interpretation and insight generation rather than data processing transformation and data processing manipulation.
- Data Storage Tasks, which emphasize data persistence and data retrieval rather than data processing operations and data processing modification.
- Data Visualization Tasks, which create visual representations rather than perform data processing transformations on underlying data.
- Data Collection Tasks (without processing), which gather raw data without applying data processing algorithms or data processing transformations.
- Data Query Tasks, which retrieve existing data without performing data processing operations or data processing modifications.
- See: Processing Task, Data Processing System, Data Processing Algorithm, Computing Task, Information Processing Task, Data Management Task, Data Engineering Task, ETL Task, Data Pipeline, Data Workflow.
References
2009
- (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=data%20processing
- S: (n) data processing ((computer science) a series of operations on data by a computer in order to retrieve or transform or classify information)
- http://en.wikipedia.org/wiki/Computer_data_processing
- Computer data processing is any process that uses a computer program to enter data and summarise, analyse or otherwise convert data into usable information. The process may be automated and run on a computer. It involves recording, analysing, sorting, summarising, calculating, disseminating and storing data. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems. Nevertheless, the terms are roughly synonymous, performing similar conversions; data-processing systems typically manipulate raw data into information, and likewise information systems typically take raw data as input to produce information as output.
Data processing may or may not be distinguished from data conversion, when the process is merely to convert data to another format, and does not involve any data manipulation.
- Computer data processing is any process that uses a computer program to enter data and summarise, analyse or otherwise convert data into usable information. The process may be automated and run on a computer. It involves recording, analysing, sorting, summarising, calculating, disseminating and storing data. Because data are most useful when well-presented and actually informative, data-processing systems are often referred to as information systems. Nevertheless, the terms are roughly synonymous, performing similar conversions; data-processing systems typically manipulate raw data into information, and likewise information systems typically take raw data as input to produce information as output.