Podcast
Questions and Answers
What is the primary goal of performing data gap analysis?
What is the primary goal of performing data gap analysis?
- To design an alert system
- To monitor model performance
- To compare available data with required datasets (correct)
- To identify the optimal ETL approach
What is the main objective of the ELT approach?
What is the main objective of the ELT approach?
- To extract, load, and transform data (correct)
- To load data into a centralized database
- To monitor data quality
- To prepare data for stakeholder review
What is a key activity in Phase 2 of the data preparation process?
What is a key activity in Phase 2 of the data preparation process?
- Designing an alert system
- Learning about the data (correct)
- Stakeholder management
- Data visualization
What is essential for ensuring data quality control?
What is essential for ensuring data quality control?
What is a benefit of using a centralized database?
What is a benefit of using a centralized database?
What is a critical aspect of stakeholder management?
What is a critical aspect of stakeholder management?
What is the primary goal of surveying and visualizing data during the data preparation phase?
What is the primary goal of surveying and visualizing data during the data preparation phase?
What is an indication of systematic error in data?
What is an indication of systematic error in data?
What is a key consideration when assessing the quality of geospatial datasets?
What is a key consideration when assessing the quality of geospatial datasets?
What is a key benefit of using data visualization tools during data preparation?
What is a key benefit of using data visualization tools during data preparation?
What is a critical aspect of data quality control during the data preparation phase?
What is a critical aspect of data quality control during the data preparation phase?
What is Schneiderman's visual analytics paradigm?
What is Schneiderman's visual analytics paradigm?
What is the purpose of a dataset inventory?
What is the purpose of a dataset inventory?
What is data transformation?
What is data transformation?
What is the purpose of reviewing data column content?
What is the purpose of reviewing data column content?
What is feature selection?
What is feature selection?
What is data integration?
What is data integration?
What is an essential consideration when assessing data quality?
What is an essential consideration when assessing data quality?
Study Notes
Data Consistency and Quality
- Systematic errors can occur due to issues with data feeds from sensors, leading to invalid, incorrect, or missing data values.
- Surveys and visualization of data can help identify outliers, skewness, and inconsistencies.
Data Preparation Key Activities
- Leverage data visualization tools to gain an overview of the data and detect outliers/skewness.
- Review data to ensure calculations remained consistent within columns or across tables for a given data field.
- Assess the granularity of the data, the range of values, and the level of aggregation of the data.
- Check for consistency of data distribution over time.
- Examine the consistency of state or country abbreviations used in geospatial datasets.
- Check if data is standardized or normalized, and if units used are consistent (e.g., metric units).
Data Gap Analysis
- Compare available data with required datasets to identify gaps.
- Identify additional data sources that can be leveraged, such as social media data for sentiment analysis.
Data Conditioning
- Data transformation involves cleaning, normalizing, and performing transformations on the data.
- Data integration involves joining or merging different datasets.
- Feature selection involves deciding which aspects of datasets to analyze or discard.
ETL vs ELT Approach
- ETL (Extract, Transform, Load) approach: data is extracted, transformed, and then loaded into a centralized database.
- ELT (Extract, Load, Transform) approach: data is extracted, loaded into a centralized database, and then transformed.
Dataset Inventory
- A dataset inventory is a structured and organized record of all datasets available within an organization.
- It helps in identifying available data sources and gaps in data.
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Description
Test your understanding of data preparation principles, including data consistency, error detection, and visualization techniques. Learn how to identify systematic errors and leverage data visualization tools to gain insights into data. Master Schneiderman's visual analytics paradigm and more.
