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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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Data Analytics Engineers - Salaries

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#Data Analytics Engineers - Salaries and career options: Some key skills which are very crucial for an employee these days are the ability to communicate disruptive ideas, multi-disciplinary skills with appropriate depth of specialisation, learnability and resilience," said Prithvi Shergill, chief human resources officer, HCL Technologies, the country's fifth-largest technology company. So, an engineer with 2-3 years' experience working in data analytics can expect a salary of Rs 4-6 lakh in India and $70-80,000 in the US or Europe.  But without big data skills, the same engineer can earn only Rs 3-5 lakh, according to Anurag Gupta, chief operating officer at Magna Infotech, an IT staffing firm. Experience of 5-6 years in data analytics can help an engineer command a salary of up to Rs 10-12 lakh in the domestic market, according to Kamal Karanth, India MD of staffing firm Kelly Services. Firms like IPsoft, Happiest Minds and Mu Sigma, operating in automati...
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