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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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Trending IT Skills Grab Opportunities

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Great demand for Mobile developers and Security professionals. Read my other article on "15 Rapidly Growing IT Jobs". Growing areas are in Internet of things and 3D printing. Then we need to know what is 3D printing? 3D printing is not necessarily transforming IT. It’s that it's a new technology that's transforming other industries like manufacturing and biomedical sectors," Laura McGarrity, vice president of digital marketing strategy for Mondo, told eWEEK. "It does create new job growth within the IT industry. Benefits to consumers include the ability to try and re-work prototypes before going to the market - consumers can expect products made for their specific needs. An excellent growth for Data related and Statistics jobs. Data and statistics are everywhere now, and there is high demand for scientists who can analyze the data," she said. "A data scientist needs to be able to manage data, create predictions, and communicate the res...
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