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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...
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Business Vs Demographic Vs Product Analytics

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List of top analytics areas and their differences



1. Analytics in Business

  • Advertising Analytics
  • Brand Analytics
  • Promotion Analytics
  • Business-to-business marketing Analytics
  • Social Media Analytics
  • Tracking Studies

2. Demographic Analytics

  • Consumer Analytics
  • Concept Testing Data Mining
  • Customer Satisfaction Study Analytics
  • Demographic Analytics
  • Employee Satisfaction Analysis
  • Text Mining
  • Ethnographic Analytics
  • Media Testing
  • Opinion Polling and Predictive Analytics
  • Usage & Attitude Studies
  • Segmentation Analytics
  • Semiotic and Cultural Analysis

3. Product Analytics

  • Packaging and Design Effectiveness Analytics
  • New Product Development
  • Pricing Studies
  • Product Testing
  • Scenario Planning 

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