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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

The best answer for 'Efficient Workbook' in Tableau

There are several factors that define an “efficient” workbook. Some of these factors are technical and some more user-focused. An efficient workbook is:

  • A workbook that takes advantage of the “principles of visual analysis” to effectively communicate the message of the author and the data, possibly by engaging the user in an interactive experience.
  • A workbook that responds in a timely fashion. This can be a somewhat subjective measure, but in general we would want the workbook to provide an initial display of information and to respond to user interactions within a couple of (< 5) seconds. 
  • Tableau latest version is 9.1.2 as on writing this post
  • Tableau version 8 and Version 9 differences
  1. Individual Query time improved by 10x
  2. Dashboard Query times improved by 9x
  3. Query Fusion improving times by 2x
  4. And Query Caching improving times by 50x

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