Podcast
Questions and Answers
What is the primary focus of the preparation stage in the data lifecycle?
What is the primary focus of the preparation stage in the data lifecycle?
- Removing data from the system permanently
- Enhancing completeness and integrity of data (correct)
- Sharing data with external users
- Creating calculated fields for data synthesis
Which step in the data lifecycle involves moving data from active systems to passive systems?
Which step in the data lifecycle involves moving data from active systems to passive systems?
- Publication
- Capture
- Purging
- Archival (correct)
What is NOT a characteristic of the purging stage in the data lifecycle?
What is NOT a characteristic of the purging stage in the data lifecycle?
- Data is still actively used by the business (correct)
- Removal of data from the system
- There is no legal requirement for the data
- Data becomes useless
Which of the following best describes the Extract, Transform, Load (ETL) process?
Which of the following best describes the Extract, Transform, Load (ETL) process?
What distinguishes active data collection from passive data collection?
What distinguishes active data collection from passive data collection?
Flashcards
Data Lifecycle
Data Lifecycle
The process of managing data from its creation to its disposal. This involves defining data needs, capturing it, preparing it, analyzing it, and ultimately purging it when no longer useful.
Data Definition
Data Definition
The first step in the Data Lifecycle, where you determine what type of information a business needs to achieve its goals.
Extract, Transform, Load (ETL)
Extract, Transform, Load (ETL)
The process of gathering and transforming data into a usable format for analysis and decision-making.
Active Data Collection
Active Data Collection
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Passive Data Collection
Passive Data Collection
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Study Notes
Data Lifecycle Process
- The Data Lifecycle Process (DCP) has eight stages: Definition, Capture, Preparation, Synthesis, Analytics and Usage, Publication, Archival, and Purging.
Definition Stage
- Identifying the specific data needed by the business.
Capture/Creation Stage
- Creating internal data or collecting from external resources.
Preparation Stage
- Improving data completeness and accuracy. This includes data integration, cleaning, and encryption. Moving data introduces potential risks.
Synthesis Stage
- Creating calculated fields to enhance data usability.
Analytics and Usage Stage
- Utilizing data for internal company purposes. (Optional step)
Publication Stage
- Sharing data with external users/customers.
Archival Stage
- Moving data from active to passive systems, freeing up resources.
Purging Stage
- Removing useless data from the system when no legal or other requirements exist.
Data Collection Types
- Extract, Transform, Load (ETL): Collecting data from sources, transforming it, and loading it into a new system.
- Extract: Gathers and retrieves data.
- Transform: Converts data into a usable format.
- Load: Transfers data into an analytical system for use.
- Active Data Collection: Obtaining data directly from employees, customers, or users.
- Passive Data Collection: Collecting data without direct permission, such as through website cookies or AI algorithms.
Complexities of External Data Sources
- Potential copyright issues.
- Safety and security concerns.
- Integrity and accuracy issues.
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Description
Explore the comprehensive stages of the Data Lifecycle Process (DCP), including Definition, Capture, Preparation, Synthesis, Analytics and Usage, Publication, Archival, and Purging. This quiz will test your understanding of each stage's importance and function in data management.
