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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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Google Analytics - Training.PDF

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Google Analytics can track data from a shopping cart on your own or other, domains with the addition of some code. If your website initiates a purchase checkout process on a separate store site (for example, if you send customers from www.mystore.com to www.securecart.com), you just have to add some tracking code to your store site and the shopping cart pages on the host site. The specific code can be found in the Analytics Help Center in the article titled, “How do I use Google Analytics to track a 3rd-party shopping cart?” Read more here: http://static.googleusercontent.com/media/www.google.com/en//grants/education/Google_Analytics_Training.pdf
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